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Relevant bibliographies by topics / Two Dimensional Discrete Wavelet Transform

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Academic literature on the topic 'Two Dimensional Discrete Wavelet Transform'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Two Dimensional Discrete Wavelet Transform"

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SUN, YANKUI, YONG CHEN, and HAO FENG. "TWO-DIMENSIONAL STATIONARY DYADIC WAVELET TRANSFORM, DECIMATED DYADIC DISCRETE WAVELET TRANSFORM AND THE FACE RECOGNITION APPLICATION." International Journal of Wavelets, Multiresolution and Information Processing 09, no. 03 (2011): 397–416. http://dx.doi.org/10.1142/s0219691311004110.

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Currently, two-dimensional dyadic wavelet transform (2D-DWT) is habitually considered as the one presented by Mallat, which is defined by an approximation component, two detail components in horizontal and vertical directions. This paper is to introduce a new type of two-dimensional dyadic wavelet transform and its application so that dyadic wavelet can be studied and used widely furthermore. (1) Two-dimensional stationary dyadic wavelet transform (2D-SDWT) is proposed, it is defined by approximation coefficients, detail coefficients in horizontal, vertical and diagonal directions, which is es

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Kimura, Motoaki, Masahiro Takei, Chih-Ming Ho, Yoshifuru Saito, and Kiyoshi Horii. "Visualization of Shear Stress With Micro Imaging Chip and Discrete Wavelet Transform." Journal of Fluids Engineering 124, no. 4 (2002): 1018–24. http://dx.doi.org/10.1115/1.1516599.

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The two-dimensional low-speed structure of a turbulent boundary layer has been clearly visualized by a combination of a shear stress sensor using micro electro mechanical systems and the discrete wavelet transform. The application of two-dimensional discrete wavelet transforms to the visualization of wall shear stress data obtained using the micro shear stress imaging chip is described. The experiment was carried out under various Reynolds number conditions. It is shown that it is possible to visualize the low-speed streak structure as contours of two-dimensional wavelet level corresponding to

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Asamoah, F. "Discrete Wavelet Analysis of Two-Dimensional Signals." International Journal of Electrical Engineering & Education 39, no. 2 (2002): 162–74. http://dx.doi.org/10.7227/ijeee.39.2.8.

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Discrete wavelet transform using Daubechies coefficients is applied to decompose a two-dimensional signal into levels. Examples are given using BMP images of a sheep and a thumbprint. The size of the two- dimensional signal is 2N by M. It is shown that it is not necessary for M to be a power of 2. A MATLAB program is written for the computations involved.

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Nahar, A. K. "A Compression Original Image Based On The DDWT Technique And Enhancement SNR." International Journal of Engineering Technology and Sciences 5, no. 3 (2018): 73–89. http://dx.doi.org/10.15282/ijets.v5i3.1132.

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Generally, Discrete wavelet transform (DWT) are good perform a when little to no simple mathematical operations in the wavelet basis, in many applications, wavelet transforms can be severely truncated compressed and retain useful information Image compression. Though, DWT and the divided wavelet transform, still suffering from Poor directionality Lack of phase information, and Shift- sensitivity, which is a major drawback in most the communications systems. The Double-Density Discrete Wavelet Transform (DDDWT) achieves great results compared to previous conventional methods less complexity. Cr

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Po-Cheng Wu and Liang-Gee Chen. "An efficient architecture for two-dimensional discrete wavelet transform." IEEE Transactions on Circuits and Systems for Video Technology 11, no. 4 (2001): 536–45. http://dx.doi.org/10.1109/76.915359.

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Shama, Kumara, and Rohan Pinto. "An efficient VLSI architecture for two-dimensional discrete wavelet transform." International Journal of High Performance Systems Architecture 8, no. 3 (2018): 179. http://dx.doi.org/10.1504/ijhpsa.2018.10022496.

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Wang, Ning, and Chungu Lu. "Two-Dimensional Continuous Wavelet Analysis and Its Application to Meteorological Data." Journal of Atmospheric and Oceanic Technology 27, no. 4 (2010): 652–66. http://dx.doi.org/10.1175/2009jtecha1338.1.

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Abstract The two-dimensional continuous wavelet transform (2D CWT) has become an important tool to examine and diagnose nonstationary datasets on the plane. Compared with traditional spectral analysis methods, the 2D CWT provides localized spectral information of the analyzed dataset. It also has the advantage over the 2D discrete wavelet transform (DWT) in that it covers the domain of the analyzed data with a continuous analysis from which detailed, shift-invariant spectral information of different positions and orientations can be obtained. In this paper, a brief introduction of the 2D CWT a

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Pang, Qilong, Liangjie Kuang, Youlin Xu, and Xiang Dai. "Study on the extraction and reconstruction of arbitrary frequency topography from precision machined surfaces." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 233, no. 7 (2018): 1772–80. http://dx.doi.org/10.1177/0954405418802307.

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This article presents an extraction and reconstruction method for arbitrary two-dimensional and three-dimensional frequency features in precision machined surfaces. A combination of power spectrum density and continuous wavelet transform is used to analyze the potassium dihydrogen phosphate crystal surface topography. All frequencies involved in sampling area of measuring instrument are distinguished by power spectrum density method. Compared to discrete wavelet transform used to decompose frequency features, continuous wavelet transform method can extract and reconstruct two-dimensional profi

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Ďuriš, Viliam, Vladimir I. Semenov, and Sergey G. Chumarov. "Wavelets and digital filters designed and synthesized in the time and frequency domains." Mathematical Biosciences and Engineering 19, no. 3 (2022): 3056–68. http://dx.doi.org/10.3934/mbe.2022141.

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<abstract> <p>The relevance of the problem under study is due to the fact that the comparison is made for wavelets constructed in the time and frequency domains. The wavelets constructed in the time domain include all discrete wavelets, as well as continuous wavelets based on derivatives of the Gaussian function. This article discusses the possibility of implementing algorithms for multiscale analysis of one-dimensional and two-dimensional signals with the above-mentioned wavelets and wavelets constructed in the frequency domain. In contrast to the discrete wavelet transform (Malla

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Zhao, Di. "Mobile GPU Computing Based Filter Bank Convolution for Three-Dimensional Wavelet Transform." International Journal of Mobile Computing and Multimedia Communications 7, no. 2 (2016): 22–35. http://dx.doi.org/10.4018/ijmcmc.2016040102.

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Mobile GPU computing, or System on Chip with embedded GPU (SoC GPU), becomes in great demand recently. Since these SoCs are designed for mobile devices with real-time applications such as image processing and video processing, high-efficient implementations of wavelet transform are essential for these chips. In this paper, the author develops two SoC GPU based DWT: signal based parallelization for discrete wavelet transform (sDWT) and coefficient based parallelization for discrete wavelet transform (cDWT), and the author evaluates the performance of three-dimensional wavelet transform on SoC G

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Dissertations / Theses on the topic "Two Dimensional Discrete Wavelet Transform"

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McCanny, P. "Generic silicon architectures for the two-dimensional discrete wavelet transform." Thesis, Queen's University Belfast, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403167.

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Legaspi, Joey E. "One and two dimensional discrete wavelet transforms." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23739.

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Benderli, Oguz. "A Real-time, Low-latency, Fpga Implementation Of The Two Dimensional Discrete Wavelet Transform." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1056282/index.pdf.

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This thesis presents an architecture and an FPGA implementation of the two dimensional discrete wavelet transformation (DWT) for applications where row-based raw image data is streamed in at high bandwidths and local buffering of the entire image is not feasible. The architecture is especially suited for multi-spectral imager systems, such as on board an imaging satellite, however can be used in any application where time to next image constraints require real-time processing of multiple images. The latency that is introduced as the images stream through the iii DWT module and the amount of lo

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Talavašek, Kamil. "Srovnání implementací diskrétní waveletové transformace v Javě a C/C++." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217186.

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This thesis deals with discrete wavelet transform of a two dimensional discrete signal using the CDF9/7 wavelet. It contains theoretical principles of discrete wavelet transformation, a description of the convolution and Lifting calculation principle, characteristics of the CDF9/7 wavelet, the possibilities of processing a two dimensional input signal and boundary handling. Both principles (convolution, Lifting) of the calculation of two dimensional discrete wavelet transformation have been implemented within the thesis using the CDF9/7 wavelet in the C++ and Java programming languages. Four a

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Cook, James Allen. "A decompositional investigation of 3D face recognition." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16653/1/James_Allen_Cook_Thesis.pdf.

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Automated Face Recognition is the process of determining a subject's identity from digital imagery of their face without user intervention. The term in fact encompasses two distinct tasks; Face Verficiation is the process of verifying a subject's claimed identity while Face Identification involves selecting the most likely identity from a database of subjects. This dissertation focuses on the task of Face Verification, which has a myriad of applications in security ranging from border control to personal banking. Recently the use of 3D facial imagery has found favour in the research community

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Cook, James Allen. "A decompositional investigation of 3D face recognition." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16653/.

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Automated Face Recognition is the process of determining a subject's identity from digital imagery of their face without user intervention. The term in fact encompasses two distinct tasks; Face Verficiation is the process of verifying a subject's claimed identity while Face Identification involves selecting the most likely identity from a database of subjects. This dissertation focuses on the task of Face Verification, which has a myriad of applications in security ranging from border control to personal banking. Recently the use of 3D facial imagery has found favour in the research community

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Andhavarapu, Sarat Kiran. "Image Blur Detection with Two-Dimensional Haar Wavelet Transform." DigitalCommons@USU, 2015. https://digitalcommons.usu.edu/etd/4443.

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Efficient detection of image blur and its extent is an open research problem in computer vision. Image blur has a negative impact on image quality. Blur is introduced into images due to various factors including limited contrast, improper exposure time or unstable device handling. Toward this end, an algorithm is presented for image blur detection with the use of Two-Dimensional Haar Wavelet transform (2D HWT). The algorithm is experimentally compared with two other image blur detection algorithms frequently cited in the literature. When evaluated over a sample of images, the algorithm perform

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Shah, Rajul R. (Rajul Ramesh) 1979. "Hardware implementation of a low-power two-dimensional discrete cosine transform." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/16859.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.<br>Includes bibliographical references (p. 143-144).<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>In this project, a JPEG compliant, low-power dedicated, two-dimensional, Discrete Cosine Transform (DCT) core meeting all IBM Softcore requirements is developed. Power is optimized completely at the algorithmic, architectural, and logic levels. The architecture uses row-column

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Gu, Siying. "VLSI systolic array architectures for the one-dimensional and two-dimensional discrete Fourier transform." Thesis, University of Ottawa (Canada), 1993. http://hdl.handle.net/10393/6711.

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In this thesis, we propose efficient systolic array architectures for the 1-D and the 2-D discrete Fourier transforms (DFT) using the second-order Goertzel algorithm. For the 1-D DFT, two 1-D and one 2D systolic arrays are proposed. The two 1-D structures, a semi-systolic array and a pure-systolic array, are characterized by regular, modular cell interconnections, thus making the arrays compatible with VLSI design principles. These arrays perform at an effective throughput rate of one DFT sample per clock cycle. The proposed 2-D array structure obtains a higher throughput rate of one DFT trans

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Srinivasan, Nirmala. "Cross-Correlation Of Biomedical Images Using Two Dimensional Discrete Hermite Functions." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1341866987.

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Books on the topic "Two Dimensional Discrete Wavelet Transform"

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Legaspi, Joey E. One and two dimensional discrete wavelet transforms. Naval Postgraduate School, 1992.

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Li, Quanrong. Design and performance estimation of two-dimensional discrete cosine transform. 1996.

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Birney, Keith Andrew. Aspects of modeling subband decomposition signals and two-dimensional discrete cosine transform coefficients for image coding. 1991.

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Book chapters on the topic "Two Dimensional Discrete Wavelet Transform"

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AlEnzi, Venus, Mohanad Alfiras, and Falah Alsaqre. "Face Recognition Algorithm Using Two Dimensional Principal Component Analysis Based on Discrete Wavelet Transform." In Digital Information Processing and Communications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22389-1_38.

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Błażewicz, Marek, Miłosz Ciżnicki, Piotr Kopta, Krzysztof Kurowski, and Paweł Lichocki. "Two-Dimensional Discrete Wavelet Transform on Large Images for Hybrid Computing Architectures: GPU and CELL." In Euro-Par 2011: Parallel Processing Workshops. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29737-3_53.

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Saadatmorad, Morteza, Ramazan-Ali Jafari-Talookolaei, Mohammad-Hadi Pashaei, Samir Khatir, and Magd Abdel Wahab. "Delamination Detection of Rectangular Laminated Composite Plates by Combining the One-Dimensional and Two-Dimensional Discrete Wavelet Transforms." In Proceedings of the 10th International Conference on Fracture Fatigue and Wear. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7808-1_5.

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Bose, Subash Chandra, Murugesh Veerasamy, Azath Mubarakali, Ninoslav Marina, and Elena Hadzieva. "Analysis of Feature Extraction Algorithm Using Two Dimensional Discrete Wavelet Transforms in Mammograms to Detect Microcalcifications." In Computational Vision and Bio-Inspired Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37218-7_4.

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Rao, K. R., D. N. Kim, and J. J. Hwang. "Two-Dimensional Discrete Fourier Transform." In Fast Fourier Transform - Algorithms and Applications. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-1-4020-6629-0_5.

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Hoseini, M. R., and M. J. Zuo. "Gearbox Fault Diagnosis Using Two-Dimensional Wavelet Transform." In Lecture Notes in Mechanical Engineering. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4993-4_55.

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Lyubin, Pavel, and Eugeny Shchetinin. "Fast Two-Dimensional Smoothing with Discrete Cosine Transform." In Communications in Computer and Information Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51917-3_55.

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Sedukhin, S. G. "Systolic array architecture for two-dimensional discrete Fourier transform." In CONPAR 90 — VAPP IV. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-53065-7_144.

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Zhang, Yu, Mei-Xing Qi, and Li Shang. "Palmprint Recognition Based on Two-Dimensional Gabor Wavelet Transform and Two-Dimensional Principal Component Analysis." In Advanced Intelligent Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24728-6_55.

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Dokur, Zümray, and Tamer Ölmez. "Recursive Form of the Discrete Fourier Transform for Two-Dimensional Signals." In Intelligent Data Engineering and Automated Learning — IDEAL 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45675-9_83.

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Conference papers on the topic "Two Dimensional Discrete Wavelet Transform"

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Imai, Yamato, Minoru Komatsu, and Hiroki Matsumoto. "Two-scale Sequence Generation Method Using Machine Learning for Discrete Wavelet Transform." In 2024 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2024. https://doi.org/10.1109/ispacs62486.2024.10868080.

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Khan, Mohammed Saquib, and Ashok Kumar Reddy Chavva. "Two-Dimensional Discrete Cosine Transform OFDM Waveform for 6G: Operation and Implementation." In 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC). IEEE, 2025. https://doi.org/10.1109/ccnc54725.2025.10975934.

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Krishnaswamy, D., and M. Orchard. "Parallel Algorithms for the Two-Dimensional Discrete Wavelet Transform." In 1994 International Conference on Parallel Processing Vol. 3. IEEE, 1994. http://dx.doi.org/10.1109/icpp.1994.148.

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Zeki Konyar, Mehmet, Omer Sayli, and Sarp Erturk. "Pseudocoloring ultrasound images with two dimensional Discrete Wavelet Transform." In 2015 Medical Technologies National Conference (TIPTEKNO). IEEE, 2015. http://dx.doi.org/10.1109/tiptekno.2015.7374596.

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Qu, Guihong, Dali Zhang, and Pingfan Yan. "Medical image fusion using two-dimensional discrete wavelet transform." In Multispectral Image Processing and Pattern Recognition, edited by Deren Li, Jie Yang, Jufu Feng, and Shen Wei. SPIE, 2001. http://dx.doi.org/10.1117/12.440275.

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Jinook Song and In-Cheol Park. "Implementation of efficient architecture of two-dimensional discrete wavelet transform." In 2008 International SoC Design Conference (ISOCC). IEEE, 2008. http://dx.doi.org/10.1109/socdc.2008.4815749.

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Tian, Xin, Jiaolong Wei, and Jinwen Tian. "Memory-Efficient Architecture for Fast Two-Dimensional Discrete Wavelet Transform." In 2010 International Conference on Computational Intelligence and Software Engineering (CiSE). IEEE, 2010. http://dx.doi.org/10.1109/cise.2010.5677178.

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Cohen, Jack K., and Tong Chen. "Quantitative dip bounds for the two-dimensional discrete wavelet transform." In SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, edited by Sergio E. Zarantonello. SPIE, 1993. http://dx.doi.org/10.1117/12.164841.

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Koko, Ibrahim Saeed, and Herman Agustiawan. "Pipelined Lifting-Based VLSI Architecture for Two-Dimensional Inverse Discrete Wavelet Transform." In 2008 International Conference on Computer and Electrical Engineering (ICCEE). IEEE, 2008. http://dx.doi.org/10.1109/iccee.2008.14.

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Yoshida, Taichi, Taizo Suzuki, Seisuke Kyochi, and Masaaki Ikehara. "Two dimensional non-separable adaptive directional lifting structure of discrete wavelet transform." In ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5946785.

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Reports on the topic "Two Dimensional Discrete Wavelet Transform"

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Derbentsev, V., A. Ganchuk, and Володимир Миколайович Соловйов. Cross correlations and multifractal properties of Ukraine stock market. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1117.

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Recently the statistical characterizations of ﬁnancial markets based on physics concepts and methods attract considerable attentions. The correlation matrix formalism and concept of multifractality are used to study temporal aspects of the Ukraine Stock Market evolution. Random matrix theory (RMT) is carried out using daily returns of 431 stocks extracted from database time series of prices the First Stock Trade System index (www.kinto.com) for the ten-year period 1997-2006. We ﬁnd that a majority of the eigenvalues of C fall within the RMT bounds for the eigenvalues of random correlation matr

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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are ob

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