Advanced Digital Imaging Laboratory - (Iop Imaging Engineering) 2nd Edition by Leonid P Yaroslavsky (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br>Advanced Digital Imaging Laboratory Using MATLAB(R), second edition, expands on the practical experience in digital imaging techniques covered by the first edition and includes formulation of the major theoretical results that underlie the exercises as well as introducing modern concepts and new techniques and numerous MATLAB(R) exercises.<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>The first edition of this text book focussed on providing practical hands-on experience in digital imaging techniques and while the book concentrated on practical applications, it kept to an absolute minimum a detailed discussion of the underlying theory. In this new extended, self-contained edition, the author builds on the strength of the original edition by expanding the coverage to include verbal formulations and intuitive explanations of major theoretical results that underlie the exercises.</p> <p>Addressing image digitization (discretization, quantization, compression), digital image formation and computational imaging, image resampling and building continuous image models, image and noise statistical characterization and diagnostics, statistical image models and pattern formation, image correlators for localization of objects, methods of image perfecting (denoizing, deblurring), methods of image enhancement and supplemented with more than 100 exercises in MATLAB(R) in all major topics of the subject, this text enables readers to master digital imaging on both fundamental theoretical and practical levels. Key features include: </p> <ul> <li>Supports studying of all aspects of digital imaging from image signal digitization to image parameter estimation, recovery, restoration and enhancement.</li> <li>New exercises that make a bridge between classical sampling and sampled image representation and modern ideas of image sparse approximation.</li> <li>Image digitization and methods of image perfecting extended to color and stereo images and supplemented with corresponding new exercises.</li> <li>Image digitization now includes coherent radiation-based imaging methods such as holography, synthetic aperture and ultrasound.</li> <li>New exercises to illustrate image rescaling with arbitrary scale factors and image denoizing by means of correlational averaging that relate to modern "non-local" denoizing methods.</li> <li>An option has been added in all exercises to save results of processing.</li> <li>MATLAB(R) source codes for more than 100 exercises are provided, which readers can modify for their particular needs and tastes, to design new exercises and, in addition, to use them for solving particular image-processing tasks.</li> <li>Test signals and images provided in the book, as well as methodology of the experiments, will be useful for readers in their further studies and practical work.</li> </ul> <p>The book offers a unique combination of theory, exercises, supportive software and data set that can be used not only for studying the subject, but also in further practical work.</p>
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