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Books on the topic 'Application to image restoration'

Author: Grafiati

Published: 12 April 2025

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1

Zelensky, Alexander A., 1943- author and Kravchenko, Viktor F., 1939- author, eds. Bispectral methods of signal processing: Applications in radar, telecommunications and digital image restoration. Berlin: Walter de Gruyter GmbH & Co. KG, 2015.

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2

Favaro, Paolo. 3-D shape estimation and image restoration: Exploiting defocus and motion blur. London: Springer, 2007.

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3

Lesk, Michael. Image formats for preservation and access: A report. Washington, D.C: Commission on Preservation and Access, 1990.

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4

Dobreva, Milena P. Applications of computer tools in studying medieval Slavonic manuscripts. Sofia, Bulgaria: Boyko Kacharmazov, 1995.

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5

Katsaggelos, Aggelos K., ed. Digital Image Restoration. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5.

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6

1956-, Katsaggelos Aggelos Konstantinos, ed. Digital image restoration. Berlin: Springer-Verlag, 1991.

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7

J, McDonnell M., ed. Image restoration and reconstruction. Oxford [Oxfordshire]: Clarendon Press, 1986.

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8

Hunter, Michael. The Image of Restoration Science. London ; New York : Routledge, 2017.: Routledge, 2016. http://dx.doi.org/10.4324/9781315556857.

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9

Olson, Rex. Professional Photoshop: Image restoration & repair. Burbank, Calif: Desktop Images, 2002.

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10

Rütimann, Hans. Computerization project of the Archivo General de Indias, Seville, Spain: A report to the Commission on Preservation and Access. Washington, D.C: Commission on Preservation and Access, 1992.

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11

1938-, Stark Henry, ed. Image recovery--theory and application. Orlando: Academic Press, 1987.

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12

Henry, Stark, ed. Image recovery: Theory and application. Orlando, Fla: Academic Press, 1987.

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13

1958-, Sezan M. Ibrahim, ed. Selected papers on digital image restoration. Bellingham, Wash., USA: SPIE Optical Engineering Press, 1992.

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14

Yuval, Fisher, ed. Fractal image compression: Theory and application. New York: Springer-Verlag, 1995.

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15

Lemeshewsky, George. Iterative restoration deblurring of SPOT panchromatic images. Reston, VA: U.S. Geological Survey, 1993.

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16

Vyas, Aparna, Soohwan Yu, and Joonki Paik. Multiscale Transforms with Application to Image Processing. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7272-7.

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17

M, Stanislas, Kompenhans Jürgen 1946-, and Westerweel J, eds. Particle image velocimetry: Progress towards industrial application. Dordrecht: Kluwer Academic Publishers, 2000.

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18

Stanislas, M. Particle Image Velocimetry: Progress towards Industrial Application. Dordrecht: Springer Netherlands, 2000.

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19

Cox, Philip William. Application of image analysis to fungal fermentations. Birmingham: University of Birmingham, 2000.

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20

Prabahan, Basu, ed. Information theoretic approaches to signal and image restoration. Bellingham, Wash: SPIE, 2011.

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21

A, Hanjalic, ed. Image and video databases: Restoration, watermarking, and retrieval. Amsterdam: Elsevier Science B. V., 2000.

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22

Miller, Brett A. Divine apology: The discourse of religious image restoration. Westport, CT: Praeger, 2003.

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23

Moayeri, Nader. An algorithm for blind restoration of blurred and noisy images. Palo Alto, CA: Hewlett-Packard Laboratories, Technical Publications Department, 1996.

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24

Histace, Aymeric, ed. Image Restoration - Recent Advances and Applications. InTech, 2012. http://dx.doi.org/10.5772/2389.

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25

Image restoration: Fundamentals and advances. Boca Raton, FL: CRC Press, 2012.

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26

Putting Image Repair to the Test: Applications of Image Restoration. Lexington Books/Fortress Academic, 2015.

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27

Rajakumar, P. S., S. Geetha, and T. V. Ananthan. Fundamentals of Image Processing. Jupiter Publications Consortium, 2023. http://dx.doi.org/10.47715/jpc.b.978-93-91303-80-8.

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Abstract:

"Fundamentals of Image Processing" offers a comprehensive exploration of image processing's pivotal techniques, tools, and applications. Beginning with an overview, the book systematically categorizes and explains the multifaceted steps and methodologies inherent to the digital processing of images. The text progresses from basic concepts like sampling and quantization to advanced techniques such as image restoration and feature extraction. Special emphasis is given to algorithms and models crucial to image enhancement, restoration, segmentation, and application. In the initial segments, the intricacies of digital imaging systems, pixel connectivity, color models, and file formats are dissected. Following this, image enhancement techniques, including spatial and frequency domain methods and histogram processing, are elaborated upon. The book then addresses image restoration, discussing degradation models, noise modeling, and blur, and offers insights into the compelling world of multi-resolution analysis with in-depth discussions on wavelets and image pyramids. Segmentation processes, especially edge operators, boundary detections, and thresholding techniques, are detailed in subsequent chapters. The text culminates by diving deep into the applications of image processing, exploring supervised and unsupervised learning, clustering algorithms, and various classifiers. Throughout the discourse, practical examples, real-world applications, and intuitive diagrams are integrated to facilitate an enriched learning experience. This book stands as an essential guide for both novices aiming to grasp the basics and experts looking to hone their knowledge in image processing. Keywords: Digital Imaging Systems, Image Enhancement, Image Restoration, Multi-resolution Analysis, Wavelets, Image Segmentation, Feature Extraction, SIFT, SURF, Image Classifiers, Supervised Learning, Clustering Algorithms.

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28

Caldiero, Chris, William L. Benoit, Joseph R. Blaney, Lauren Alwine, and Joseph D. Blosenhauer. Putting Image Repair to the Test: Quantitative Applications of Image Restoration Theory. Lexington Books/Fortress Academic, 2015.

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29

Soatto, Stefano, and Paolo Favaro. 3-D Shape Estimation and Image Restoration. Springer, 2008.

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30

Kwan, Chiman, ed. Recent Advances in Image Restoration with Applications to Real World Problems. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.90607.

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31

Kwan, Chiman. Recent Advances in Image Restoration with Applications to Real World Problems. IntechOpen, 2020.

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32

Ardouin, Jean-Pierre. A model for an ultrasonic phased-array B-scan imaging system and its application to image restoration. 1986.

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33

Gibbs, Alison L. Convergence of Markov Chain Monte Carlo algorithms with applications to image restoration. 2000.

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34

Gibbs, Alison L. Convergence of Markov chain Monte Carlo algorithms with applications to image restoration. 2000, 2000.

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35

Totsky, Alexander V., Alexander A. Zelensky, and Victor F. Kravchenko. Bispectral Methods of Signal Processing: Applications in Radar, Telecommunications and Digital Image Restoration. de Gruyter GmbH, Walter, 2014.

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36

Totsky, Alexander V., Alexander A. Zelensky, and Victor F. Kravchenko. Bispectral Methods of Signal Processing: Applications in Radar, Telecommunications and Digital Image Restoration. de Gruyter GmbH, Walter, 2014.

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37

Bispectral Methods of Signal Processing: Applications in Radar, Telecommunications and Digital Image Restoration. De Gruyter, Inc., 2015.

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38

Soatto, Stefano, and Paolo Favaro. 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur. Springer, 2013.

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39

Soatto, Stefano, and Paolo Favaro. 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur. Springer, 2007.

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40

Soatto, Stefano, and Paolo Favaro. 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur. Springer, 2006.

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41

Gunturk, Bahadir Kursat. Image Restoration. CRC Press, 2012. http://dx.doi.org/10.1201/b12693.

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42

Gunturk, Bahadir Kursat. Image Restoration. Taylor & Francis Group, 2012.

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43

Katsaggelos, Aggelos K. Digital Image Restoration. Springer, 1991.

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44

Katsaggelos, Aggelos K. Digital Image Restoration. Springer, 2012.

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45

Zervakis, Michael E. Nonlinear image restoration techniques. 1990.

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46

J, McDonnell M., ed. Image restoration and reconstruction. Clarendon, 1989.

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47

Stanimirovic?, Ivan. Image Recognition and Restoration. Arcler Education Inc, 2018.

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48

Li, Xin, and Bahadir Kursat Gunturk. Image Restoration: Fundamentals and Advances. Taylor & Francis Group, 2017.

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49

Li, Xin, and Bahadir Kursat Gunturk. Image Restoration: Fundamentals and Advances. Taylor & Francis Group, 2018.

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50

Li, Xin, and Bahadir Kursat Gunturk. Image Restoration: Fundamentals and Advances. Taylor & Francis Group, 2018.

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