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Author: John W. Woods
ISBN : B00BCRO7L8
New from $78.94
Format: PDF, EPUB
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This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms.
This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams.
New to this edition:
- New appendices on random processes, information theory
- New coverage of image analysis - edge detection, linking, clustering, and segmentation
- Expanded coverage on image sensing and perception, including color spaces.
- Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC.
- Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding.
- More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming.
- New coverage of super-resolution methods for image and video.
- Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected.
- New chapters on introductory random processes, information theory, and image enhancement and analysis
- Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC)
Direct download links available for Free Download Multidimensional Signal, Image, and Video Processing and Coding
- File Size: 8185 KB
- Print Length: 616 pages
- Publisher: Academic Press; 2 edition (May 31, 2011)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B00BCRO7L8
- Text-to-Speech: Enabled
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- Lending: Not Enabled
- Amazon Best Sellers Rank: #1,072,936 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Free Download Multidimensional Signal, Image, and Video Processing and Coding
Woods offers an intense mathematical treatment of numerous methods of doing signal analysis. Here the input can be a two dimensional image, which in itself is a vast field of filter design, using Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters. The nice aspect of dealing with these images is that at least you can readily get feedback in the form of processed images. Which also attests to the practical value of the often intricate calculations.
The book prefers Matlab as the backing software engine. These days, at least at the level of this book, you should not need to write all your own code. Matlab has tons of subroutines prebuilt for analysis. What the book does is help you understand and use them.
The advantage of having Matlab compared to not using any package is apparent if you have tried learning from texts on this subject from 20 years or more ago. Then, the maths could be arbitrarily involved, but it was difficult to translate that into functioning code that you could then apply and see the results. Matlab lets you close this loop far more easily.
The text also delves into image enhancement and analysis. The distinction between these might be lost to many. But in this field, the analysis is the harder problem. It tries to work backwards from a 2d image to, in some cases, derive the 3 dimensional structure that gave rise to the image. While the full case is probably ill determined and unsolvable, the narrative describes several very useful simple algorithms that tackle low level tasks like object segmentation.
Bayesian analysis is another key idea for you to assimilate. The description is good but necessarily brief.
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