Technical Book "Introduction to Image Quality Improvement, Image Restoration, and Super-Resolution Technology"
WS264 *Available for preview
~Easy-to-understand explanation with MATLAB program demo~ *Available for preview.
*Publication Date: February 4, 2011 *Format: B5 size, 131 pages, with supplementary CD (includes MATLAB program code) *Price: 52,290 yen (including tax) *Author Chen Yanwei, Professor, Department of Media Informatics, College of Information Science and Engineering, Ritsumeikan University (Doctor of Engineering) <Author's Biography> 1985: Graduated from Kobe University, Faculty of Engineering 1987: Completed Master's Program at Osaka University Graduate School of Engineering 1990: Completed Doctoral Program at Osaka University Graduate School of Engineering, Doctor of Engineering 1991: Researcher at the Laser Technology Comprehensive Research Institute 1994: Lecturer at the Department of Electrical and Electronic Engineering, University of the Ryukyus 1996: Associate Professor at the Department of Electrical and Electronic Engineering, University of the Ryukyus 2003: Professor at the Department of Electrical and Electronic Engineering, University of the Ryukyus 2004: Professor at the Department of Media Informatics, College of Information Science and Engineering, Ritsumeikan University
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basic information
In an information-oriented society, the media of "images" has been receiving increasing attention. Particularly in recent years, the acceleration of the internet and the proliferation of high-performance personal computers have made digital image processing more accessible. Today's image processing technologies are utilized in various fields such as medical image diagnosis, satellite image processing, surveillance cameras, and digital TV broadcasting; however, the image quality and resolution obtained from current cameras and imaging devices are often not sufficient. Therefore, there is a high demand for image quality improvement through image processing technologies, especially in light of the recent trend towards high-definition and the improvement of image resolution in related devices (HDTV, digital cameras, etc.). The image quality enhancement and super-resolution technology discussed in this book are receiving significant attention. In recent years, the author has held seminars on super-resolution technology several times a year for corporate technology developers, undergraduate and graduate students, providing lectures that cover everything from the basics to the latest technologies, often incorporating practical exercises. Due to requests from many participants for more detailed materials and programs, this publication was developed in collaboration with Trikepus to compile the content of the seminar lectures into a book.
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52,290 yen (including tax)
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P2
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P2
Applications/Examples of results
Chapter 1: Image Processing and Image Degradation Models Chapter 2: Noise Reduction Techniques 1. Filtering and Convolution Operations 2. Gaussian Filter 3. Bilateral Filter 4. Smoothing Filter Based on Anisotropic Diffusion 5. Wavelet Shrinkage Filter 6. ICA Shrinkage Filter Chapter 3: Image Restoration Techniques 1. Degraded Images and Point Spread Function 2. Inverse Filter and Wiener Filter 3. Iterative Back Projection Method 4. Blind Deconvolution of Defocused Images Based on Edge Detection 5. Learning-Based Blind Deconvolution 6. Blind Deconvolution of Pinhole Camera Images Using Cepstrum Chapter 4: Basics of Geometric Transformations, Registration Techniques, and Interpolation Techniques 1. Geometric Transformations 2. Registration Techniques 3. Interpolation Techniques Chapter 5: Super-Resolution Techniques 1. Multi-Frame Super-Resolution Techniques 2. Hierarchical Super-Resolution Techniques for High Magnification Image Generation 3. Super-Resolution Techniques Using Reconstruction Methods 4. Case-Based Super-Resolution Techniques 5. Learning-Based Super-Resolution Techniques 6. Face Hallucination Super-Resolution Techniques
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