Littérature scientifique sur le sujet « Image processin »

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Articles de revues sur le sujet "Image processin"

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Jung, Sun Ho. "Study on CCTV based Sensor applied SURF Image Processin System." KOREA SCIENCE & ART FORUM 16 (June 30, 2014): 403. http://dx.doi.org/10.17548/ksaf.2014.06.16.403.

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Barrera-Fernández, Daniel, and Kevin Meethan. "The Relationship of City Branding and Tourist Promotion: The Case of Plymouth (UK) and Malaga (Spain)." Athens Journal of Tourism 1, no. 3 (2014): 217–25. https://doi.org/10.5281/zenodo.13735705.

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In the global market cities compete in the brand image they create,this message has to be convincing and precise. In order to build -images just a few urban features are chosen, which can be materialsuch as built heritage, infrastructure or iconic architecture.However, non-material aspects like historic references, an attractiveway of life and cultural values are becoming crucial when trying tolink local economic strategies and tourist promotion, particularlywhen specializing in urban tourism segments such as history andculture, meetings, incentives, conferences and events. To create thissymbo
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Bhuvaneswari, M. "Gaussian mixture model: An application to parameter estimation and medical image classification." Journal of Scientific and Innovative Research 5, no. 3 (2016): 100–105. http://dx.doi.org/10.31254/jsir.2016.5308.

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Gaussian mixture model based parameter estimation and classification has recently received great attention in modelling and processin g data. Gaussian Mixture Model (GMM) is the probabilistic model for representing the presence of subpopulations and it works well with the classification and parameter estimation strategy. Here in this work Maximum Likelihood Estimation (MLE) based on Expectation Maximization (EM) is being used for the parameter estimation approach and the estimated parameters are being used for the training and the testing of the images for their normality and the abnormality.
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Nivetha., I., and M. Padmaa Dr. "Disease Detection in Tree Leaves and Fruits using Image Processing Techniques." Journal of Radio and Television Broadcast 3, no. 3 (2018): 24–28. https://doi.org/10.5281/zenodo.2293551.

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<em>India is the agriculture based country. Now a day, agricultural product yield is decrease for the reason of disease affect the plants like fungus, virus diseases. In this paper, we detect the tree leaves and fruits disease using image processing techniques. In this paper apple, grapes and pomegranate disease are detected. The apple diseases are apple scab, apple rot, Marssonina leaf blotch, black rot canker, apple mosaic. The grape diseases are black rot, powdery mildew, downy mildew, anthracnose, bacterial leaf spot, and rust. The pomegranate diseases are bacterial blight, aspergillus fru
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Legland, David, and Marie-Françoise Devaux. "ImageM: a user-friendly interface for the processing of multi-dimensional images with Matlab." F1000Research 10 (April 30, 2021): 333. http://dx.doi.org/10.12688/f1000research.51732.1.

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Modern imaging devices provide a wealth of data often organized as images with many dimensions, such as 2D/3D, time and channel. Matlab is an efficient software solution for image processing, but it lacks many features facilitating the interactive interpretation of image data, such as a user-friendly image visualization, or the management of image meta-data (e.g. spatial calibration), thus limiting its application to bio-image analysis. The ImageM application proposes an integrated user interface that facilitates the processing and the analysis of multi-dimensional images within the Matlab env
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Pariyar, Kopila. "Process of Detecting Barcodes Using Image Processing." International Journal of Scientific Engineering and Research 2, no. 7 (2014): 18–19. https://doi.org/10.70729/j2013326.

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Oguma, Ryuichiro, Syo Matsumura, and Tetsuo Eguchi. "Mesoscopic TDGL Model for Formation of Domain Structures in D019 Type Ordering." Solid State Phenomena 172-174 (June 2011): 602–7. http://dx.doi.org/10.4028/www.scientific.net/ssp.172-174.602.

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The present authors recently presented the time-dependent Ginzburg-Landau (TDGL) formulation for L12 type ordering processin binary alloys, taking into account the symmetrical relationships of these ordered phases. Extending the formulation, the authors have developed the TDGL model for microstructural evolution of D019 type ordering. The D019 structure based on hcp is divided into four equivalent sublattices. The site occupation probabilities are given as a function of three order parameters and a composition parameter. Multiple types of variants of the structures are represented by the order
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Mohamed Y Abdallah, Yousif, Mohamed MO Yousef, and Eltayeb W Eltayeb. "Automated Enhancement of Myocardium Images using Image Processing Methods." International Journal of Science and Research (IJSR) 10, no. 7 (2021): 557–64. https://doi.org/10.21275/sr21709185141.

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Alessandro, Massaro, Vitti Valeria, and Galiano Angelo. "Automatic Image Processing Engine Oriented on Quality Control of Electronic Boards." Signal & Image Processing : An International Journal (SIPIJ) 9, no. 2 (2019): 1–14. https://doi.org/10.5281/zenodo.3243307.

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ABSTRACT We propose in this work a study of an image processing engine able to detect automatically the features of electronic board weldings. The engine has been developed by using ImageJ and OpenCV libraries. Specifically the image processing segmentation has been improved by watershed approach. After a complete design of the automation processes, different test have been performed showing the engine efficiency in terms of features extraction, scale setting and thresholding calibration. The engine provides as outputs the storage of the cropped images of each single defects. The proposed engi
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Shete, S. G., and Nagnath G. Ghadge. "Image Processing in MATLAB 9.3." International Journal of Trend in Scientific Research and Development 2, no. 2 (2018): 925–29. https://doi.org/10.31142/ijtsrd9545.

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In this paper we introduce how to handle different kinds of image formats in MATLAB 9.3 by using Matlab Workspace and its Various Commands. Also we illustrated example of processing the images. Shete S. G. | Ghadge Nagnath G. &quot;Image Processing in MATLAB 9.3&quot; Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: https://www.ijtsrd.com/papers/ijtsrd9545.pdf
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Thèses sur le sujet "Image processin"

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Bergström, Britt, and Erica Burlin. "Bildens godkännandeprocessi katalogproduktion : The image approval processin a catalog production." Thesis, Högskolan Dalarna, Grafisk teknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4210.

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The objective of this thesis has been to investigate the approval process for an image. This investigation has been carriedout at four catalog-producing companies and three companies working with repro or printing. The information wasgathered through interviews and surveys and later used for evaluation. The result of the evaluation has shown that allbusinesses are very good at technical aspects but also that the biggest problem they have is with the communication. Theconclusion is that businesses need a clear construction for the image process. This will minimize the communicationproblems and
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Murphy, Brian P. "Image processing techniques for acoustic images." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/26585.

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Approved for public release; distribution is unlimited<br>The primary goal of this research is to test the effectiveness of various image processing techniques applied to acoustic images generated in MATLAB. The simulated acoustic images have the same characteristics as those generated by a computer model of a high resolution imaging sonar. Edge Detection and Segmentation are the two image processing techniques discussed in this study. The two methods tested are a modified version of the Kalman filtering and median filtering
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Khan, Preoyati. "Cluster Based Image Processing for ImageJ." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1492164847520322.

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Yallop, Marc Richard. "Image processing techniques for passive millimetre wave images." Thesis, University of Reading, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409545.

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Baabd, A., M. Y. Tymkovich, and О. Г. Аврунін. "Image Processing of Panoramic Dental X-Ray Images." Thesis, ХГУ, 2018. http://openarchive.nure.ua/handle/document/6204.

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The panoramic image allows to clearly see the state of the teeth, the dental rudiments, which are located in the jaw, temporomandibular joints, as well as the maxillary sinuses. It is noted that this type of study has a small dose of radiation. Indications for this type of study are dental implantation, bite correction, suspicion of bone tissue inflammation, control of the growth and development of the teeth, as well as the diagnosis of other dental problems.
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AbouRayan, Mohamed. "Real-time Image Fusion Processing for Astronomical Images." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1461449811.

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Kim, Younhee. "Towards lower bounds on distortion in information hiding." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3403.

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Thesis (Ph.D.)--George Mason University, 2008.<br>Vita: p. 133. Thesis directors: Zoran Duric, Dana Richards. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Title from PDF t.p. (viewed Mar. 17, 2009). Includes bibliographical references (p. 127-132). Also issued in print.
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Tummala, Sai Virali, and Veerendra Marni. "Comparison of Image Compression and Enhancement Techniques for Image Quality in Medical Images." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15360.

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Acosta, Edward Kelly. "A programmable processor for the Cheops image processing system." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36557.

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Abdulla, Ghaleb. "An image processing tool for cropping and enhancing images." Master's thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-12232009-020207/.

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Livres sur le sujet "Image processin"

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Kayyali, Mohamed S. Digital image processing. Facultad de Ingenieria y Arquitectura de la Universidad de San Martin de Porres, 2002.

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Dougherty, Edward R. Random processes for image and signal processing. SPIE Optical Engineering Press, 1999.

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Goudail, François, and Philippe Réfrégier. Statistical Image Processing Techniques for Noisy Images. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-8855-3.

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El-Sharkawy, Mohamed. Signal processing, image processing, and graphics applications with Motorola's DSP96002 processor. PTR Prentice Hall, 1994.

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Acharya, Tinku, and Ajoy K. Ray. Image Processing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471745790.

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Petrou, Maria, and Pedro García Sevilla. Image Processing. John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/047003534x.

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E, Pearson D., ed. Image processing. McGraw-Hill, 1991.

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National Institutes of Health (U.S.). Division of Computer Research and Technology., ed. Image processing. Division of Computer Research and Technology, National Institutes of Health, 1985.

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Henri, Maître, ed. Image processing. ISTE Ltd., 2008.

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Acharya, Tinku. Image Processing. John Wiley & Sons, Ltd., 2005.

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Chapitres de livres sur le sujet "Image processin"

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Klemm, Anna, and Kota Miura. "Batch Processing Methods in ImageJ." In Bioimage Data Analysis Workflows ‒ Advanced Components and Methods. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-76394-7_2.

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AbstractIn this chapter you will learn how to execute a workflow on not only one image but on several images in ImageJ – a technique that is called “Batch Processing”. Various ways of doing this are possible in the Fiji distribution of ImageJ, and the characteristics of each and how-to are explained.
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Wolff, Robert S., and Larry Yaeger. "Images and Image Processing." In Visualization of Natural Phenomena. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4684-0646-7_1.

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Corke, Peter. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54413-7_12.

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Corke, Peter, Witold Jachimczyk, and Remo Pillat. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-07262-8_11.

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Corke, Peter. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-06469-2_11.

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Corke, Peter. "Images and Image Processing." In Robotic Vision. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79175-9_4.

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Cree, Michael J., and Herbert F. Jelinek. "Image Analysis of Retinal Images." In Medical Image Processing. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9779-1_11.

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Arheit, Marcel, Daniel Castaño-Díez, Raphaël Thierry, Bryant R. Gipson, Xiangyan Zeng, and Henning Stahlberg. "Image Processing of 2D Crystal Images." In Methods in Molecular Biology. Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-176-9_10.

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Hamann, Sabine, Hauke Hell, Detlef Pankow, and Robert Wunderer. "Image Processing." In DigiScript™. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-46829-2_39.

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Ortega-Alcalde, D. "Image processing." In Developments in Cardiovascular Medicine. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1984-9_2.

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Actes de conférences sur le sujet "Image processin"

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Jariwala, Devanshi, and Ruchi Gajjar. "Image Processing Based Texture Transfer Between Images." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739041.

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R, Muthuraman, Muthukumar N, Srihari R, Thileepkumar S, and Saranya C. "Efficient VLSI Implementation of Image Processing Processor Acceleration." In 2025 Third International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2025. https://doi.org/10.1109/icaiss61471.2025.11041700.

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Alu, Andrea. "Metasurfaces for Image Processing and Analog Computing." In Laser Science. Optica Publishing Group, 2024. https://doi.org/10.1364/ls.2024.lw7f.2.

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I discuss our recent progress in demonstrating ultrathin engineered surfaces that perform image processing and computing on optical signals and images, and the opportunities for photonic technologies. Full-text article not available; see video presentation
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Smuleac, Adrian, Laura Smuleac, Raul Pascalau, George Popescu, and Adina Horablaga. "USING GROUND CONTROL POINTS (GCP) AND UAV POIND CLOUD PROCESSIN� IN WATER MANAGEMENT." In 22nd International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022v/3.2/s12.27.

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Using aerial vehicles without pilot (UAV-unmanned aerial vehicle) or Drone has seen a rapid development, over the last decade, in order to obtain spatial information of the Earth's surface. This scientific paper was realized for the Hydrotechnical Node of Costei, from Timis County and has as purpose the processing of aerial images, obtained from a Phantom4 Pro device, which is capable to capture video at 4K resolution at 30 frames per second and Full HD 1080p at 120 frames per second for a slow motion with a Sony EXMOR camera that can take photos at 12 megapixels, with a maximum flight speed o
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Zhang, Chenhao, Yongzhi Jing, Jie Kong, Tao Peng, Zhenzhen Liao, and Jianhua Hao. "Method for Measuring Levitation Gap of Magnetic Levitation Ball Based on Image Processin." In 2019 3rd International Conference on Robotics and Automation Sciences (ICRAS). IEEE, 2019. http://dx.doi.org/10.1109/icras.2019.8808955.

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Taylor, T. S., M. M. Wilson, R. L. Hartman, and K. B. Farr. "Optical Disk Spatial Light Modulator." In Symposium on Optical Memory. Optica Publishing Group, 1996. http://dx.doi.org/10.1364/isom.1996.otub.6.

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Advances in technology have made optical disk technology for optical signal processing realizable. The limiting factor in optical image processing is the spatial light modulator (liquid crystal or similar devices). Higher resolution and faster filter access makes optical disk technology an attractive alternative. Images are represented onto a CD by a single stream of 1's and 0's read by the optical pickup system. Digital processing is then performed on the image. We propose to write 2-dimensional images directly to a CD as shown in Figure 1. The 2-D images can then be accessed by our optical p
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Shagalova, P. A., E. S. Sokolova, and S. N. Ryndov. "Automation of Blood Microscopy Image Processing." In 32nd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/graphicon-2022-1157-1164.

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Automation of medical image processing aims to create a universal tool for the purposes of medical diagnostics in the field of microscopy of cells and tissues. The authors of the paper have collected large databases of various digital microscopy images that allow to automate the processes of medical research using computer vision technologies, improve the quality of image analysis and provide a set of diagnostic information for decision making. For this purpose, a software package with a user-friendly interface has been developed that allows visualizing the results of detection of microobjects
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Boothroyd, S. A., P. H. Beckwith, L. Chan, and J. Chrostowski. "Multiple Grating Optical Processing in Barium Titanate." In Photorefractive Materials, Effects, and Devices II. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/pmed.1991.wc18.

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Nonlinear optical image subtraction and Boolean XOR operations have been demonstrated in Michelson interferometers with phase conjugate mirrors [1-3], The two interferometer arms each contain a light modulating transmission or reflection element which must be carefully registered and imaged at the interferometer output. Destructive interference between the output images of the two arms arises because one image undergoes a extra π phase change on reflection from a dielectric interface. Image subtraction has also been achieved in photorefractives via double exposure holography [4] where two grat
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Wong, Chan, Carlos Montes, Laine Mears, and John Ziegert. "A New Position Feedback Method for Manufacturing Equipment." In ASME 2008 International Manufacturing Science and Engineering Conference collocated with the 3rd JSME/ASME International Conference on Materials and Processing. ASMEDC, 2008. http://dx.doi.org/10.1115/msec_icmp2008-72222.

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This paper presents an innovative real time 2-dimensional position feedback method, which processes visual input data from a target image on an actively-controlled planar pixel matrix. The objective is to demonstrate the ability to position an X-Y stage with high resolution, using direct position sensing of a dynamically controlled image. In order to achieve high spatial resolution using a pixel array as a target, an algorithm that processes both the geometric shape and the grayscale intensities of the image is implemented. The test platform consists of an X-Y stage carrying a Liquid Crystal D
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Stojancic, M., and G. Eichmann. "Superresolving image restoration using an associative memory processor." In OSA Annual Meeting. Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.wt10.

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The issue of superresolving signal and image restoration appears in many areas, such as the restoration of diffraction-limited images, geophysical prospecting, radar and sonar signal processing, biomedical imaging, image and signal bandwidth compression, reconstruction of signals and images from partial and incomplete information, etc. There is a large repertoire of different techniques and procedures available to reconstruct such images. However, most of these techniques work well only in the absence of noise. Because this is an ill-posed problem, the actual reconstruction is sensitive to noi
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Rapports d'organisations sur le sujet "Image processin"

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Bickel, V. T., B. Moseley, E. Hauber, M. Shirley, J. P. Williams, and D. A. Kring. CHARACTERIZATION OF SHADOWED REGIONS AT THE LUNAR SOUTH POLE. Frontier Development Lab, 2022. http://dx.doi.org/10.56272/gqkz6227.

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This image repository contains a total of 576 non map-projected HORUS (Hyper-effective nOise Removal Unet Software) post-processed images of permanently shadowed regions (PSRs) located across the Artemis exploration zone at the lunar south pole (144 individual images).
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Allard, Anthony, Edward Dugan, and Alan Jacobs. Image Processing Techniques for Lateral Migration Radiography Land Mine Images. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada384546.

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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, 2023. http://dx.doi.org/10.3289/sw_2_2023.

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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in
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Meitzler, Thomas, Grant Gerhart, Harpreet Singh, et al. Image Processing. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada597230.

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Rosenfeld, Azriel. Parallel Image Processing and Image Understanding. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada183223.

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Rosenfeld, A. Parallel Image Processing and Image Understanding. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada159029.

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Van Eeckhout, E., P. Pope, and L. Balick. Image processing technology. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/262986.

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Chartrand, Rick. Image processing and reconstruction. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1044085.

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Khoury, Jehad, and Mark Cronin-Golomb. Real Time Holographic Image Processing. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada408111.

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Giardina, Charles R., and Edward R. Dougherty. Image Processing Language. Phase 1. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada204232.

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