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Still Image and Video Compression with MATLAB

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The term “video compression” is now a common household name. The field of still image and video compression has matured to the point that it is possible to watch movies on a laptop computer. Such is the rapidity at which technology in various fields has advanced and is advancing. However, this creates a need for some to obtain at least a simple understanding behind all this. This book attempts to do just that, to explain the theory behind still image and video compression methods in an easily understandable manner. The readers are expected to have an introductory knowledge in college-level mathematics and systems theory.

The properties of a still image are similar to those of a video, yet different. A still image is a spatial distribution of light intensity, while a video consists of a sequence of such still images. Thus, a video has an additional dimension—the temporal dimension. These properties are exploited in several different ways to achieve data compression. A particular image compression method depends on how the image properties are manipulated.

Due to the availability of efficient, high-speed central processing units (CPUs), many Internet-based applications offer software solutions to displaying video in real time. However, decompressing and displaying high-resolution video in real time, such as high-definition television (HDTV), requires special hardware processors. Several such real-time video processors are currently available off the shelf. One can appreciate the availability of a variety of platforms that can decompress and display video in real time from the data received from a single source. This is possible because of the existence of video compression standards such as Moving Picture Experts Group (MPEG).

This book first describes the methodologies behind still image and video compression in a manner that is easy to comprehend and then describes the most popular standards such as Joint Photographic Experts Group (JPEG), MPEG, and advanced video coding. In explaining the basics of image compression, care has been taken to keep the mathematical derivations to a minimum so that students as well as practicing professionals can follow the theme easily. It is very important to use simpler mathematical notations so that the reader would not be lost in a maze. Therefore, a sincere attempt has been made to enable the reader to easily follow the steps in the book without losing sight of the goal. At the end of each chapter, problems are offered so that the readers can extend their knowledge further by solving them.
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