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Cena, Bernard Maria. "Reconstruction for visualisation of discrete data fields using wavelet signal processing." University of Western Australia. Dept. of Computer Science, 2000. http://theses.library.uwa.edu.au/adt-WU2003.0014.
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The reconstruction of a function and its derivative from a set of measured samples is a fundamental operation in visualisation. Multiresolution techniques, such as wavelet signal processing, are instrumental in improving the performance and algorithm design for data analysis, filtering and processing. This dissertation explores the possibilities of combining traditional multiresolution analysis and processing features of wavelets with the design of appropriate filters for reconstruction of sampled data. On the one hand, a multiresolution system allows data feature detection, analysis and filtering. Wavelets have already been proven successful in these tasks. On the other hand, a choice of discrete filter which converges to a continuous basis function under iteration permits efficient and accurate function representation by providing a “bridge” from the discrete to the continuous. A function representation method capable of both multiresolution analysis and accurate reconstruction of the underlying measured function would make a valuable tool for scientific visualisation. The aim of this dissertation is not to try to outperform existing filters designed specifically for reconstruction of sampled functions. The goal is to design a wavelet filter family which, while retaining properties necessary to preform multiresolution analysis, possesses features to enable the wavelets to be used as efficient and accurate “building blocks” for function representation. The application to visualisation is used as a means of practical demonstration of the results. Wavelet and visualisation filter design is analysed in the first part of this dissertation and a list of wavelet filter design criteria for visualisation is collated. Candidate wavelet filters are constructed based on a parameter space search of the BC-spline family and direct solution of equations describing filter properties. Further, a biorthogonal wavelet filter family is constructed based on point and average interpolating subdivision and using the lifting scheme. The main feature of these filters is their ability to reconstruct arbitrary degree piecewise polynomial functions and their derivatives using measured samples as direct input into a wavelet transform. The lifting scheme provides an intuitive, interval-adapted, time-domain filter and transform construction method. A generalised factorisation for arbitrary primal and dual order point and average interpolating filters is a result of the lifting construction. The proposed visualisation filter family is analysed quantitatively and qualitatively in the final part of the dissertation. Results from wavelet theory are used in the analysis which allow comparisons among wavelet filter families and between wavelets and filters designed specifically for reconstruction for visualisation. Lastly, the performance of the constructed wavelet filters is demonstrated in the visualisation context. One-dimensional signals are used to illustrate reconstruction performance of the wavelet filter family from noiseless and noisy samples in comparison to other wavelet filters and dedicated visualisation filters. The proposed wavelet filters converge to basis functions capable of reproducing functions that can be represented locally by arbitrary order piecewise polynomials. They are interpolating, smooth and provide asymptotically optimal reconstruction in the case when samples are used directly as wavelet coefficients. The reconstruction performance of the proposed wavelet filter family approaches that of continuous spatial domain filters designed specifically for reconstruction for visualisation. This is achieved in addition to retaining multiresolution analysis and processing properties of wavelets.
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Chen, Shuo. "MALDI-TOF MS data processing using wavelets, splines and clustering techniques." [Johnson City, Tenn. : East Tennessee State University], 2004. http://etd-submit.etsu.edu/etd/theses/available/etd-1112104-113123/unrestricted/ChenS121404f.pdf.
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Thesis (M.S.)--East Tennessee State University, 2004.<br>Title from electronic submission form. ETSU ETD database URN: etd-1112104-113123 Includes bibliographical references. Also available via Internet at the UMI web site.
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Jung, Uk. "Wavelet-based Data Reduction and Mining for Multiple Functional Data." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5084.
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Advance technology such as various types of automatic data
acquisitions, management, and networking systems has created a
tremendous capability for managers to access valuable production
information to improve their operation quality and efficiency.
Signal processing and data mining techniques are more popular than
ever in many fields including intelligent manufacturing. As data
sets increase in size, their exploration, manipulation, and
analysis become more complicated and resource consuming. Timely
synthesized information such as functional data is needed for
product design, process trouble-shooting, quality/efficiency
improvement and resource allocation decisions. A major obstacle in
those intelligent manufacturing system is that tools for
processing a large volume of information coming from numerous
stages on manufacturing operations are not available. Thus, the
underlying theme of this thesis is to reduce the size of data in a
mathematical rigorous framework, and apply existing or new
procedures to the reduced-size data for various decision-making
purposes. This thesis, first, proposes {it Wavelet-based
Random-effect Model} which can generate multiple functional data
signals which have wide fluctuations(between-signal variations) in
the time domain. The random-effect wavelet atom position in the
model has {it locally focused impact} which can be distinguished
from other traditional random-effect models in biological field.
For the data-size reduction, in order to deal with heterogeneously
selected wavelet coefficients for different single curves, this
thesis introduces the newly-defined {it Wavelet Vertical Energy}
metric of multiple curves and utilizes it for the efficient data
reduction method. The newly proposed method in this thesis will
select important positions for the whole set of multiple curves by
comparison between every vertical energy metrics and a threshold
({it Vertical Energy Threshold; VET}) which will be optimally
decided based on an objective function. The objective function
balances the reconstruction error against a data reduction ratio.
Based on class membership information of each signal obtained,
this thesis proposes the {it Vertical Group-Wise Threshold}
method to increase the discriminative capability of the
reduced-size data so that the reduced data set retains salient
differences between classes as much as possible. A real-life
example (Tonnage data) shows our proposed method is promising.
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Leite, Ricardo Barroso 1984. "Compressão de imagens digitais combinando técnicas wavelet e wedgelet no ambiente de comunicações móveis." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260074.
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Orientadores: Yuzo Iano, Ana Lúcia Mendes Cruz Silvestre da Silva<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-18T18:35:20Z (GMT). No. of bitstreams: 1
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Previous issue date: 2011<br>Resumo: Os avanços em telecomunicações e o desenvolvimento dos equipamentos digitais impulsionaram diversas áreas de pesquisa relacionadas à codificação e compressão de imagens. Dentre as áreas de atuação destacam-se as aplicações para dispositivos móveis (celulares, smartphones, iPhones, iPads entre outros), que se caracterizam por baixas taxas de transmissão de dados. Entretanto, imagens codificadas com os padrões atualmente em estado-da-arte apresentam artefatos visuais característicos, como efeito de bloco e ringing. Para contornar a inabilidade das transformadas ortogonais em lidar com a geometria, é proposto na literatura o uso de dicionários wedgelet e da decomposição cartoon-textura. Nesse contexto, propõe-se um método de codificação híbrido wedgelet-wavelet inédito que preserva componentes de cartoon e textura, superando em qualidade visual ao uso de dicionários isolados e se aproximando do desempenho de sistemas de codificação completos, tais como o padrão JPEG 2000. Os ganhos de desempenho, principalmente em qualidade visual das imagens reconstruídas para baixas taxas de dados, indicam que a metodologia apresentada pode vir a ser incluída em sistemas de transmissão com restrições de largura de banda, como por exemplo a TV digital móvel<br>Abstract: Advances in telecommunications and the development of digital equipments have improved several research areas related to coding and image compression. Among these application fields are the mobile devices (cellphones, smartphones, iPhones, iPad, and others), characterized by low data transmission rates. However, images encoded by state-of-the-art standards present characteristic visual artifacts, like blocking and ringing effects. To surpass the disadvantages of orthogonal transforms in dealing with geometry, wedgelets dictionaries and cartoon-texture decomposition are proposed in literature. In this context, a new hybrid wedgelet-wavelet coding method that preserves cartoon and texture components is proposed, achieving better visual quality than the use of isolated dictionaries, approaching the performance of complete codification systems, such as the JPEG 2000. The performance gains, especially concerning visual quality of the reconstructed images using low data rates, show that this methodology might be adopted in restricted bandwidth transmission systems, such as the digital mobile TV<br>Mestrado<br>Telecomunicações e Telemática<br>Mestre em Engenharia Elétrica
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Hua, Li. "Vector wavelet transforms for the coding of static and time-varying vector fields." Diss., Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-05062003-120341.
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De, Voir Christopher S. "Wavelet Based Feature Extraction and Dimension Reduction for the Classification of Human Cardiac Electrogram Depolarization Waveforms." PDXScholar, 2005. https://pdxscholar.library.pdx.edu/open_access_etds/1740.
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An essential task for a pacemaker or implantable defibrillator is the accurate identification of rhythm categories so that the correct electrotherapy can be administered. Because some rhythms cause a rapid dangerous drop in cardiac output, it is necessary to categorize depolarization waveforms on a beat-to-beat basis to accomplish rhythm classification as rapidly as possible. In this thesis, a depolarization waveform classifier based on the Lifting Line Wavelet Transform is described. It overcomes problems in existing rate-based event classifiers; namely, (1) they are insensitive to the conduction path of the heart rhythm and (2) they are not robust to pseudo-events. The performance of the Lifting Line Wavelet Transform based classifier is illustrated with representative examples.
Although rate based methods of event categorization have served well in implanted devices, these methods suffer in sensitivity and specificity when atrial, and ventricular rates are similar. Human experts differentiate rhythms by morphological features of strip chart electrocardiograms. The wavelet transform is a simple approximation of this human expert analysis function because it correlates distinct morphological features at multiple scales. The accuracy of implanted rhythm determination can then be improved by using human-appreciable time domain features enhanced by time scale decomposition of depolarization waveforms.
The purpose of the present work was to determine the feasibility of implementing such a system on a limited-resolution platform. 78 patient recordings were split into equal segments of reference, confirmation, and evaluation sets. Each recording had a sampling rate of 512Hz, and a significant change in rhythm in the recording. The wavelet feature generator implemented in Matlab performs anti-alias pre-filtering, quantization, and threshold-based event detection, to produce indications of events to submit to wavelet transformation. The receiver operating characteristic curve was used to rank the discriminating power of the feature accomplishing dimension reduction. Accuracy was used to confirm the feature choice. Evaluation accuracy was greater than or equal to 95% over the IEGM recordings.
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Silva, Carlos Alexandre Moreira da 1984. "Aplicação de tecnologias analíticas de processo e inteligência artificial para monitoramento e controle de processo de recobrimento de partículas em leito fluidizado." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266036.
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Orientador: Osvaldir Pereira Taranto<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química<br>Made available in DSpace on 2018-08-27T00:40:14Z (GMT). No. of bitstreams: 1
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Previous issue date: 2015<br>Resumo: As indústrias química, alimentícia e farmacêutica têm empregado extensivamente a operação de fluidização em inúmeros processos, devido às suas características bastante atrativas, que possibilitam um contato efetivo entre a fase sólida e fluida, o que reflete na geração de altas taxas de transferência de calor e de massa. No entanto, o regime de fluidização borbulhante, o qual é condição de partida dos processos que envolvem esta operação, frequentemente é afetado pelas condições operacionais. As temperaturas elevadas, o conteúdo de umidade excessivo das partículas e a introdução de líquidos no leito fluidizado podem conduzir a instabilidades no regime fluidodinâmico e provocar o colapso parcial ou total do leito, reduzindo a eficiência do processo. A manutenção de condições estáveis do regime de fluidização durante processos de recobrimento de partículas em leitos fluidizados é de fundamental importância para garantir uma eficiência de recobrimento favorável e evitar a formação de zonas sem movimentação e aglomeração das partículas no leito, pois estes fatores indesejáveis comprometem a mistura entre as fases e conseqüentemente a qualidade do produto final. Dentro deste contexto, a utilização de um sistema de monitoramento e controle em tempo real de processos de recobrimento de partículas é extremamente desejável para permitir a operação de regimes de fluidização estáveis e garantir um filme de recobrimento uniforme e boas condições de escoabilidade dos sólidos. A presente proposta de tese de doutorado tem por objetivo aplicar a metodologia de análise espectral Gaussiana dos sinais de flutuação de pressão (Parise et al. (2008)), para o desenvolvimento de sistemas de controle baseados em inteligência artificial (Lógica Fuzzy), visando monitorar a estabilidade do regime de fluidização em processo de recobrimento de partículas. Comparações entre as condições fluidodinâmicas dos processos com e sem controle foram analisadas para operações em leito fluidizado em escala de laboratorio. Para avaliar a qualidade das partículas foi utilizada uma sonda de monitoramento in-line (Parsum IPP70), onde se pôde verificar os instantes iniciais da aglomeração indesejada. Com a aplicação desde sistema automatizado foi possível associar a estabilidade da fluidização em função do elevado grau de aglomeração. O ponto de parada do processo pôde ser definido em 420 µm (inicial em 360 µm) e a partir deste o mecanismo de recobrimento acontece simultaneamente com o de aglomeração. Os parâmetros de monitoramento do regime conseguiram não somente identificar a fase inicial da defluidização, como também foi possível a partir deles, controlar o processo por Lógica Fuzzy-PI e estabilizar a operação para altas taxas de suspensão atomizadas<br>Abstract:
The chemical, food and pharmaceutical industries have extensively used fluidization operation in many cases, due to its very attractive features that enable effective contact between the solid and fluid phase, which reflects the generation of high heat and mass transfer rates. However, the bubbling fluidization regime, which is the starting condition of the processes involved in this operation is often affected by operating conditions. Elevated temperatures, excessive moisture content of the particles and introduction of liquid into the fluidized bed may lead to instabilities in the fluid-dynamic regime and cause partial or total collapse of the bed, reducing the process efficiency. The maintenance of stable conditions of the fluidization regime for particle coating processes in fluidized beds is of fundamental importance to ensure a favorable coating efficiency and to avoid zones without movement and agglomeration of particles in the bed, because these undesirable factors compromise the mixing between the phases and therefore the quality of the final product. Within this context, the use of a monitoring system and real-time control of particle coating processes is highly desirable to allow operation in stable fluidization regimes and to ensure a uniform coating film and good condition of flowability of the solids. This doctoral thesis aims to apply the Gaussian spectral analysis methodology of the pressure fluctuation signals (Parise et al. (2008)) , for the development of control systems based on artificial intelligence (Fuzzy Logic), to monitor the stability of fluidization regime particle coating process. Comparisons between the fluid dynamic conditions of the processes with and without control were analyzed for operations in fluidized bed laboratory scale. To assess early stages of unwanted agglomeration, a monitoring in-line probe (Parsum IPP70) was used. With the application of this automated system, it was possible to associate the stability of fluidization with a high degree of agglomeration. The process stopping point could be set at 420 µm (initial in 360 µm) and after, the coating mechanism takes place simultaneously with the agglomeration one. The monitoring parameters of the system were able to identify the initial phase of defluidization, as well as it was possible to control the process by using Fuzzy Logic and to stabilize the operation for high rates of the coating suspension atomized onto the bed<br>Doutorado<br>Engenharia de Processos<br>Doutor em Engenharia Química
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Zhao, Fangwei. "Multiresolution analysis of ultrasound images of the prostate." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2004.0028.
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[Truncated abstract] Transrectal ultrasound (TRUS) has become the urologist’s primary tool for diagnosing and staging prostate cancer due to its real-time and non-invasive nature, low cost, and minimal discomfort. However, the interpretation of a prostate ultrasound image depends critically on the experience and expertise of a urologist and is still difficult and subjective. To overcome the subjective interpretation and facilitate objective diagnosis, computer aided analysis of ultrasound images of the prostate would be very helpful. Computer aided analysis of images may improve diagnostic accuracy by providing a more reproducible interpretation of the images. This thesis is an attempt to address several key elements of computer aided analysis of ultrasound images of the prostate. Specifically, it addresses the following tasks: 1. modelling B-mode ultrasound image formation and statistical properties; 2. reducing ultrasound speckle; and 3. extracting prostate contour. Speckle refers to the granular appearance that compromises the image quality and resolution in optics, synthetic aperture radar (SAR), and ultrasound. Due to the existence of speckle the appearance of a B-mode ultrasound image does not necessarily relate to the internal structure of the object being scanned. A computer simulation of B-mode ultrasound imaging is presented, which not only provides an insight into the nature of speckle, but also a viable test-bed for any ultrasound speckle reduction methods. Motivated by analysis of the statistical properties of the simulated images, the generalised Fisher-Tippett distribution is empirically proposed to analyse statistical properties of ultrasound images of the prostate. A speckle reduction scheme is then presented, which is based on Mallat and Zhong’s dyadic wavelet transform (MZDWT) and modelling statistical properties of the wavelet coefficients and exploiting their inter-scale correlation. Specifically, the squared modulus of the component wavelet coefficients are modelled as a two-state Gamma mixture. Interscale correlation is exploited by taking the harmonic mean of the posterior probability functions, which are derived from the Gamma mixture. This noise reduction scheme is applied to both simulated and real ultrasound images, and its performance is quite satisfactory in that the important features of the original noise corrupted image are preserved while most of the speckle noise is removed successfully. It is also evaluated both qualitatively and quantitatively by comparing it with median, Wiener, and Lee filters, and the results revealed that it surpasses all these filters. A novel contour extraction scheme (CES), which fuses MZDWT and snakes, is proposed on the basis of multiresolution analysis (MRA). Extraction of the prostate contour is placed in a multi-scale framework provided by MZDWT. Specifically, the external potential functions of the snake are designated as the modulus of the wavelet coefficients at different scales, and thus are “switchable”. Such a multi-scale snake, which deforms and migrates from coarse to fine scales, eventually extracts the contour of the prostate
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Shah, Vijay Pravin. "A wavelet-based approach to primitive feature extraction, region-based segmentation, and identification for image information mining." Diss., Mississippi State : Mississippi State University, 2007. http://library.msstate.edu/etd/show.asp?etd=etd-07062007-134150.
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Hloupis, Georgios. "Seismological data acquisition and signal processing using wavelets." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3470.
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This work deals with two main fields: a) The design, built, installation, test, evaluation, deployment and maintenance of Seismological Network of Crete (SNC) of the Laboratory of Geophysics and Seismology (LGS) at Technological Educational Institute (TEI) at Chania. b) The use of Wavelet Transform (WT) in several applications during the operation of the aforementioned network. SNC began its operation in 2003. It is designed and built in order to provide denser network coverage, real time data transmission to CRC, real time telemetry, use of wired ADSL lines and dedicated private satellite links, real time data processing and estimation of source parameters as well as rapid dissemination of results. All the above are implemented using commercial hardware and software which is modified and where is necessary, author designs and deploy additional software modules. Up to now (July 2008) SNC has recorded 5500 identified events (around 970 more than those reported by national bulletin the same period) and its seismic catalogue is complete for magnitudes over 3.2, instead national catalogue which was complete for magnitudes over 3.7 before the operation of SNC. During its operation, several applications at SNC used WT as a signal processing tool. These applications benefited from the adaptation of WT to non-stationary signals such as the seismic signals. These applications are: HVSR method. WT used to reveal undetectable non-stationarities in order to eliminate errors in site’s fundamental frequency estimation. Denoising. Several wavelet denoising schemes compared with the widely used in seismology band-pass filtering in order to prove the superiority of wavelet denoising and to choose the most appropriate scheme for different signal to noise ratios of seismograms. EEWS. WT used for producing magnitude prediction equations and epicentral estimations from the first 5 secs of P wave arrival. As an alternative analysis tool for detection of significant indicators in temporal patterns of seismicity. Multiresolution wavelet analysis of seismicity used to estimate (in a several years time period) the time where the maximum emitted earthquake energy was observed.
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Goldschneider, Jill R. "Lossy compression of scientific data via wavelets and vector quantization /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/5881.
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Choe, Gwangwoo. "Merged arithmetic for wavelet transforms /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004235.
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Pun, Ka-shun Carson, and 潘加信. "New design and realization techniques for perfect reconstruction two-channel filterbanks and wavelets bases." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31226632.
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Grant, Jeremy. "Wavelet-Based Segmentation of Fluorescence Microscopy Images in Two and Three Dimensions." Fogler Library, University of Maine, 2008. http://www.library.umaine.edu/theses/pdf/GrantJ2008.pdf.
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Lounsbery, John Michael. "Multiresolution analysis for surfaces of arbitrary topological type /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/6998.
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Sun, Lu. "Geometric transformation and image singularity with wavelet analysis." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/656.
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Yang, Jianwei. "Construction of wavelets based on unitary transform, permutation and matrix extension with applications to watermarking." HKBU Institutional Repository, 2005. http://repository.hkbu.edu.hk/etd_ra/617.
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Luo, Yi. "Theory and design of M-channel cosine modulated filter banks and wavelets /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19471130.
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Luvizotto, Andre Luiz. "Modelos de representação de sinais musicais via transformada Wavelets." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259755.
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Orientadores: Rafael Santos Mendes, Jonatas Manzolli<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-10T02:37:04Z (GMT). No. of bitstreams: 1
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Previous issue date: 2007<br>Resumo: Neste trabalho, as transformadas wavelet são utilizadas para recodificar e explorar sinais musicais. A idéia central do trabalho é mostrar que a reordenação adequada dos coeficientes provenientes das análises possibilita não somente recodificar de modo econômico o sinal como também transitar por sonoridades distintas. Ou seja, relaciona-se o posicionamento dos coeficientes wavelets, dentro de cada nível de multiresolução, com a geração de diferentes timbres. Uma vez definido o ordenamento dos coeficientes, duas formas de determinação de seus valores são exploradas. Na primeira forma, essas curvas ascendentes de coeficientes são aproximadas por uma função polinomial de grau p, levando a representações econômicas do sinal musical. Já no segundo modelo, os coeficientes de um sinal distinto (chamado sinal de base) são ordenados de forma ascendente. São então reordenados através das posições equivalentes do sinal original, também chamado de alvo, permitindo a sua reobtenção e também o trânsito entre as duas sonoridades envolvidas. Os resultados deste trabalho destacam a grande importância que o posicionamento dos coeficientes exercem na sonoridade com relação aos seus valores. Com os experimentos realizados, foi possível constatar que valores aproximados de coeficientes, corretamente dispostos no tempo, geram timbres alvos diversos de forma satisfatória. As análises dos resultados são feitas por metodologias diversas e pela audição dos arquivos de áudio gerados, que acompanham o texto em cd. Por fim, uma discussão sobre os resultados obtidos é realizada e uma proposta de continuação da pesquisa é sugerida, baseada em grupos de permutações como forma de síntese<br>Abstract: Musical signals are encoded and represented using wavelet transforms. Starting upon wavelet analysis, the main research idea is to show how an adequate re-ordination of wavelet coefticients makes possible to decode the signal economically and also to obtain different sonorities. Moreover, we relate a specific set of wavelet coeflicients from °each multi-resolution leveI to generate new timbres. Given re-ordination procedures, two forms to determine their values are explored. First one, coeflicient curves in ascendent order are approximated by a polynomial function of degree p that leads to an economic representation of musical signals. In the second approach, coeflicients from another signal (named "base"signal) are ordinated in ascendent order also. After they are re-ordinate across the positions ofthe original signal, called "target"signal. The results ofthis research highlight the great importance of the wavelet coeflicient's order to manipulate timbre. Experiments presented . here showed that coeflicients with approximated values and correct1y disposed in time, can be used to generate target timbres in a satisfactory way. The analysis of the results were done by different methodologies and by listening to the sound examples from the CD attached to this dissertation. Finally, a discussion of research aims is presented and a proposal for further work based on Mathematical Group of Permutation is projected as a way to develop a new synthesis method<br>Mestrado<br>Engenharia de Computação<br>Mestre em Engenharia Elétrica
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May, Heather. "Wavelet-based Image Processing." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037498.
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Tourshan, Khaled. "Parameterization of slant and slantlet/wavelet transforms with applications /." Thesis, Connect to Dissertations & Theses @ Tufts University, 2003.
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Thesis (Ph.D.)--Tufts University, 2003.<br>Adviser: Joseph P. Noonan. Submitted to the Dept. of Electrical Engineering. Includes bibliographical references (leaves 149-149). Access restricted to members of the Tufts University community. Also available via the World Wide Web;
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Luo, Yi, and 羅毅. "Theory and design of M-channel cosine modulated filter banks and wavelets." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215634.
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Chan, Chi-wing. "Design of 1-D and 2-D perfect reconstruction filter banks /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20717908.
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Belayneh, Sirak. "The identity of zeros of higher and lower dimensional filter banks and the construction of multidimensional nonseparable wavelets." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3417.
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Thesis (Ph.D.)--George Mason University, 2008.<br>Vita: p. 160. Thesis director: Edward J. Wegman. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Technology. Title from PDF t.p. (viewed Mar. 9, 2009). Includes bibliographical references (p. 151-159). Also issued in print.
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Jeong, Myong-Kee. "Wavelet-Based Methodology in Data Mining for Complicated Functional Data." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5148.
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To handle potentially large size and complicated
nonstationary functional data, we present the wavelet-based methodology in data mining for process monitoring and fault classification. Since traditional wavelet shrinkage methods for
data de-noising are ineffective for the more demanding data reduction goals, this thesis presents data reduction methods based on discrete wavelet transform. Our new methods minimize objective functions to balance the tradeoff between data reduction and modeling accuracy. Several evaluation studies with four popular
testing curves used in the literature and with two real-life data sets demonstrate the superiority of the proposed methods to
engineering data compression and statistical data de-noising methods that are currently used to achieve data reduction goals. Further experimentation in applying a classification tree-based data mining procedure to the reduced-size data to identify process fault classes also demonstrates the excellence of the proposed
methods. In this application the proposed methods, compared with analysis of original large-size data, result in lower misclassification rates with much better computational efficiency.
This thesis extends the scalogram's ability for handling noisy and possibly massive data which show time-shifted patterns. The proposed thresholded scalogram is built on the fast wavelet
transform, which can effectively and efficiently capture non-stationary changes in data patterns. Finally, we present a SPC procedure that adaptively determines which wavelet coefficients
will be monitored, based on their shift information, which is estimated from process data. By adaptively monitoring the process,
we can improve the performance of the control charts for functional data. Using a simulation study, we compare the performance of some of the recommended approaches.
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Liu, Xiaoqiu. "Microscopic tissue image processing for pathological evaluation /." free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9999304.
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Argus, Markus. "Machine learning for wavelets to enhance PET reconstruction." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-182932.
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In the field of Nuclear Medicine, positron emission tomography (PET) plays an important role as one of the most common diagnostic tools in the area of medical imaging. However, various physical degradation factors occur when the data is recorded, which leads to a low signal-to-noise ratio. This makes the quality of the PET images less than optimal. The proposed method for solving this problem is to use a machine learning approach to find a sparse representation of the sinograms. Where a suitable sparse representation should retain as much of the signal and as little of the noise as possible. To accomplish this a sparse autoencoder was trained on wavelet decompositions of sinograms simulated from medical images in order to learn underlying structures. Three different wavelet families were tested, Daubechies 4, biorthogonal 4.4, and Haar. The trained model was able to find sparse representations of the input sinograms in the wavelet domain. Although the sparse autoencoder managed to learn the basic structures of the sinograms, it struggled with the more complex details. Compared to a conventional denoising method using hard thresholding the sparse autoencoder did not manage to produce as good of a result in terms of the reconstructed PET image quality.
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Valdivia, Paola Tatiana Llerena. "Graph signal processing for visual analysis and data exploration." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-15102018-165426/.
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Signal processing is used in a wide variety of applications, ranging from digital image processing to biomedicine. Recently, some tools from signal processing have been extended to the context of graphs, allowing its use on irregular domains. Among others, the Fourier Transform and the Wavelet Transform have been adapted to such context. Graph signal processing (GSP) is a new field with many potential applications on data exploration. In this dissertation we show how tools from graph signal processing can be used for visual analysis. Specifically, we proposed a data filtering method, based on spectral graph filtering, that led to high quality visualizations which were attested qualitatively and quantitatively. On the other hand, we relied on the graph wavelet transform to enable the visual analysis of massive time-varying data revealing interesting phenomena and events. The proposed applications of GSP to visually analyze data are a first step towards incorporating the use of this theory into information visualization methods. Many possibilities from GSP can be explored by improving the understanding of static and time-varying phenomena that are yet to be uncovered.<br>O processamento de sinais é usado em uma ampla variedade de aplicações, desde o processamento digital de imagens até a biomedicina. Recentemente, algumas ferramentas do processamento de sinais foram estendidas ao contexto de grafos, permitindo seu uso em domínios irregulares. Entre outros, a Transformada de Fourier e a Transformada Wavelet foram adaptadas nesse contexto. O Processamento de Sinais em Grafos (PSG) é um novo campo com muitos aplicativos potenciais na exploração de dados. Nesta dissertação mostramos como ferramentas de processamento de sinal gráfico podem ser usadas para análise visual. Especificamente, o método de filtragem de dados porposto, baseado na filtragem de grafos espectrais, levou a visualizações de alta qualidade que foram atestadas qualitativa e quantitativamente. Por outro lado, usamos a transformada de wavelet em grafos para permitir a análise visual de dados massivos variantes no tempo, revelando fenômenos e eventos interessantes. As aplicações propostas do PSG para analisar visualmente os dados são um primeiro passo para incorporar o uso desta teoria nos métodos de visualização da informação. Muitas possibilidades do PSG podem ser exploradas melhorando a compreensão de fenômenos estáticos e variantes no tempo que ainda não foram descobertos.
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陳志榮 and Chi-wing Chan. "Design of 1-D and 2-D perfect reconstruction filter banks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31214915.
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Kim, Il-Ryeol. "Wavelet domain partition-based signal processing with applications to image denoising and compression." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 2.98 Mb., 119 p, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3221054.
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Liao, Zhiwu. "Image denoising using wavelet domain hidden Markov models." HKBU Institutional Repository, 2005. http://repository.hkbu.edu.hk/etd_ra/616.
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Jose, Adarsh. "Gene selection by 1-D discrete wavelet transform for classifying cancer samples using DNA microarray data." Akron, OH : University of Akron, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=akron1240851642.
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Dissertation (Ph. D.)--University of Akron, Dept. of Chemical and Biomedical Engineering, 2009.<br>"May, 2009." Title from electronic dissertation title page (viewed 8/3/2009) Advisor, Dale H. Mugler; Co-advisor, Zhong-Hui Duan; Committee members, Daniel B. Sheffer; Department Chair, Daniel B. Sheffer; Dean of the College, George K. Haritos; Dean of the Graduate School, George R. Newkome. Includes bibliographical references.
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Silwal, Sharad Deep. "Bayesian inference and wavelet methods in image processing." Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/2355.
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Tabb, Jeremiah R. "Using wavelets and principle components analysis to model data from simulated sheet forming processes." Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/10146.
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Fekri, Faramarz. "Finite-field wavelet transforms and their application to error-control coding." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/15799.
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Wu, Jiangfeng. "Wavelet packet division multiplexing." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0002/NQ42889.pdf.
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Ni, Jiangqun, and 倪江群. "Study of wavelet and the filter bank theory with application to image coding." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31237599.
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吳寶明 and Baoming Wu. "Image-based monitoring and wavelet multi-rhythm analysis of long-term locomotor activity." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31242467.
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Wu, Baoming. "Image-based monitoring and wavelet multi-rhythm analysis of long-term locomotor activity." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23273148.
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Shi, Fangmin. "Wavelet transforms for stereo imaging." Thesis, University of South Wales, 2002. https://pure.southwales.ac.uk/en/studentthesis/wavelet-transforms-for-stereo-imaging(65abb68f-e30b-4367-a3a8-b7b3df85f566).html.
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Stereo vision is a means of obtaining three-dimensional information by considering the same scene from two different positions. Stereo correspondence has long been and will continue to be the active research topic in computer vision. The requirement of dense disparity map output is great demand motivated by modern applications of stereo such as three-dimensional high-resolution object reconstruction and view synthesis, which require disparity estimates in all image regions. Stereo correspondence algorithms usually require significant computation. The challenges are computational economy, accuracy and robustness. While a large number of algorithms for stereo matching have been developed, there still leaves the space for improvement especially when a new mathematical tool such as wavelet analysis becomes mature. The aim of the thesis is to investigate the stereo matching approach using wavelet transform with a view to producing efficient and dense disparity map outputs. After the shift invariance property of various wavelet transforms is identified, the main contributions of the thesis are made in developing and evaluating two wavelet approaches (the dyadic wavelet transform and complex wavelet transform) for solving the standard correspondence problem. This comprises an analysis of the applicability of dyadic wavelet transform to disparity map computation, the definition of a waveletbased similarity measure for matching, the combination of matching results from different scales based on the detectable minimum disparity at each scale and the application of complex wavelet transform to stereo matching. The matching method using the dyadic wavelet transform is through SSD correlation comparison and is in particular detailed. A new measure using wavelet coefficients is defined for similarity comparison. The approach applying a dual tree of complex wavelet transform to stereo matching is formulated through phase information. A multiscale matching scheme is applied for both the matching methods. Imaging testing has been made with various synthesised and real image pairs. Experimental results with a variety of stereo image pairs exhibit a good agreement with ground truth data, where available, and are qualitatively similar to published results for other stereo matching approaches. Comparative results show that the dyadic wavelet transform-based matching method is superior in most cases to the other approaches considered.
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Farnham, Rodrigo Bouchardet. "Processing and inpainting of sparse data as applied to atomic force microscopy imaging." California State University, Long Beach, 2013.
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Fernandes, Junior Antonio Carlos Lopes 1976. "Contribuições ao problema de extração de tempo musical." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260786.
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Orientadores: Furio Damiani, Romis Ribeiro de Faissol Attux<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-27T01:42:11Z (GMT). No. of bitstreams: 1
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Previous issue date: 2015<br>Resumo: A deteção de tempo em um sinal musical é uma tarefa muito importante em diversas aplicações. A presente tese apresenta os resultados da detecção de andamento usando uma nova abordagem baseada na extração de atributos de um conjunto de funções de detecção de periodicidade e aprendizado de máquina. Para isto a transformada wavelet foi utilizada para separar o sinal musical em diferentes resoluções e o domínio complexo retificado foi aplicado para a construção de funções de deteccão de onsets. Em seguida, as funções de deteccão de periodicidade para cada nível wavelet foram geradas por operações de autocorrelação. Descritores de áudio clássicos foram adaptados e extraídos de cada função de periodicidade e foram usados como entradas para a máquina de aprendizado que mapeia os descritores para o tempo da música. As máquinas utilizadas foram o perceptron de múltiplas camadas e a máquina de aprendizado extremo, com propostas diferenciadas de configuração. Um método para classificação e avaliação dos descritores foi proposto. Também, neste trabalho, um novo descritor foi proposto. Um método de seleção forward de atributos via Gram-Schmidt foi aplicado para a escolha do melhor subconjunto para o treinamento da máquina. Foi ainda aplicado um método de clustering via K-means para a partilha de observações entre os conjuntos de treinamento, teste e validação, e foi proposto um novo método de seleção de observações via análise de componentes principais denominado de seleção esférica de observações<br>Abstract: Tempo detection in a music signal is a very important task for many applications. This thesis presents results concerning this task using a new approach based on the extraction of features from a set of periodicity detection functions and on machine learning. The wavelet transform was utilized to separate the musical signal at different resolutions and the rectified complex domain was applied to the construction of onset detection functions. Then, periodicity detection functions for each resolution were generated by autocorrelation operations. Classic audio features were extracted from each periodicity function and were used as inputs to a neural network that maps descriptors to music tempo. The used machines were the multilayer perceptron and an extreme learning machine, with different configuration proposals. A method for classification and evaluation of features has been proposed. Also, in this work, a new descriptor has been proposed. A method of forward selection via Gram-Schmidt was applied to choosing the best subset for the machine training. A K-means clustering method was also applied for partitioning observations between the training sets and a new observation selection method via principal component analysis, called spherical selection of observations, was proposed<br>Doutorado<br>Eletrônica, Microeletrônica e Optoeletrônica<br>Doutor em Engenharia Elétrica
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García, Antonio. "Parallel time varying volume rendering on tile displays." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1135801433.
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Larico, Chavez Roger Fredy. "Contribuições para pós processamento da transformada wavelet na codificação roi e spiht com aplicação na transmissão de imagens." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260500.
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Orientador: Yuzo Iano<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-19T20:29:50Z (GMT). No. of bitstreams: 1
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Previous issue date: 2012<br>Resumo: A área que trata de compressão de imagem com perdas é, atualmente, de grande importância. Isso se deve ao fato de que as técnicas de compressão permitem representar de uma forma eficiente uma imagem reduzindo assim, o espaço necessário para armazenamento ou um posterior envio da imagem através de um canal de comunicações. Em particular, o algoritmo SPIHT (Set Partitioning of Hierarchical Trees) muito usado em compressão de imagens é de implementação simples e pode ser aproveitado em aplicações onde se requer uma baixa complexidade. Este trabalho propõe um esquema de compressão de imagens utilizando uma forma personalizada de armazenamento da transformada DWT (Discrete Wavelet Transform), codificação flexível da ROI (Region Of Interest) e a compressão de imagens usando o algoritmo SPIHT. A aplicação consiste na transmissão dos dados correspondentes usando-se codificação turbo. A forma personalizada de armazenamento da DWT visa um melhor aproveitamento da memória por meio do uso de algoritmo SPIHT. A codificação ROI genérica é aplicada em um nível alto da decomposição DWT. Nesse ponto, o algoritmo SPIHT serve para ressaltar e transmitir com prioridade as regiões de interesse. Os dados a serem transmitidos, visando o menor custo de processamento, são codificados com um esquema turbo convolucional. Isso porque esse esquema é de implementação simples no que concerne à codificação. A simulação é implementada em módulos separados e reutilizáveis para esta pesquisa. Os resultados das simulações mostram que o esquema proposto é uma solução que diminui a quantidade de memória utilizada bem como o custo computacional para aplicações de envio de imagens em aplicações como transmissão de imagens via satélite, radiodifusão e outras mídias<br>Abstract: Nowadays, the area that comes to lossy image compression is really important. This is due to the fact that compression techniques allow an efficient way to represent an image thereby reducing the space required for storage or subsequent submission of an image through a communications channel. In particular, the algorithm SPIHT (Set Partitioning of Hierarchical Trees) widely used in image compression is simple to implement and can be used in applications where a low complexity is required. This study proposes an image compression scheme using a personalized storage transform DWT (Discrete Wavelet Transform), encoding flexible ROI (Region Of Interest) and image compression algorithm using SPIHT. The application consists in a transmission of the corresponding data using turbo coding. The shape of the custom storage DWT aims to make better use of memory by reducing the amount of memory through the use of SPIHT algorithm. ROI coding is applied in a generic high-level DWT decomposition. At this point, the algorithm serves to highlight SPITH and transmit the priority areas of interest. The data to be transmitted in order to lower the cost of processing are encoded with a turbo convolutional scheme. This is due this scheme is simple to implement with regard to coding. The simulation is implemented in separate modules and reusable for this research. The simulations and analysis show that the proposed scheme is a solution that decreases the amount of memory used and the computational cost for applications to send images in applications such as image transmission via satellite, broadcasting and others medias<br>Doutorado<br>Telecomunicações e Telemática<br>Doutor em Engenharia Elétrica
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Sun, Zhi. "Wavelet packet based structural health monitoring and damage assessment /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202003%20SUN.
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Rucker, Justin Thomas. "3D wavelet-based algorithms for the compression of geoscience data." Master's thesis, Mississippi State : Mississippi State University, 2005. http://sun.library.msstate.edu/ETD-db/ETD-browse/browse.
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Lutz, Steven S. "Hokua – A Wavelet Method for Audio Fingerprinting." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3247.pdf.
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Long, Zhiling. "Statistical image modeling in the contourlet domain with application to texture segmentation." Diss., Mississippi State : Mississippi State University, 2007. http://library.msstate.edu/etd/show.asp?etd=etd-11082007-161335.
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Turkmen, Muserref. "Digital Image Processing Of Remotely Sensed Oceanographic Data." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609948/index.pdf.
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Developing remote sensing instrumentation allows obtaining information about an area rapidly and with low costs. This fact offers a challenge to remote sensing algorithms aimed at extracting information about an area from the available re¬<br>mote sensing data. A very typical and important problem being interpretation of satellite images. A very efficient approach to remote sensing is employing discrim¬<br>inant functions to distinguish different landscape classes from satellite images. Various methods on this direction are already studied. However, the efficiency of the studied methods are still not very high. In this thesis, we will improve efficiency of remote sensing algorithms. Besides we will investigate improving boundary detection methods on satellite images.
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Lee, Kichun. "Functional data mining with multiscale statistical procedures." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34716.
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Hurst exponent and variance are two quantities that often characterize real-life, highfrequency
observations. We develop the method for simultaneous estimation of a timechanging
Hurst exponent H(t) and constant scale (variance) parameter C in a multifractional
Brownian motion model in the presence of white noise based on the asymptotic behavior of
the local variation of its sample paths. We also discuss the accuracy of the stable and simultaneous
estimator compared with a few selected methods and the stability of computations
that use adapted wavelet filters.
Multifractals have become popular as flexible models in modeling real-life data of high
frequency. We developed a method of testing whether the data of high frequency is consistent
with monofractality using meaningful descriptors coming from a wavelet-generated multifractal
spectrum. We discuss theoretical properties of the descriptors, their computational
implementation, the use in data mining, and the effectiveness in the context of simulations,
an application in turbulence, and analysis of coding/noncoding regions in DNA sequences.
The wavelet thresholding is a simple and effective operation in wavelet domains that selects
the subset of wavelet coefficients from a noised signal. We propose the selection of this
subset in a semi-supervised fashion, in which a neighbor structure and classification function
appropriate for wavelet domains are utilized. The decision to include an unlabeled coefficient
in the model depends not only on its magnitude but also on the labeled and unlabeled
coefficients from its neighborhood. The theoretical properties of the method are discussed
and its performance is demonstrated on simulated examples.