Titlebook: Real-Time Video Compression; Techniques and Algor Raymond Westwater,Borko Furht Book 1997 Springer Science+Business Media New York 1997 Sta

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VLSI Architectures for the XYZ Video Codec, search for motion estimation. Total MOPS requirements for both the encoder and decoder are 1,166 MOPS. If the exhaustive search was used for motion estimation, this number would be much higher — 7,550 MOPS.

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The Problem of Video Compression,e has been, to a substantial degree, embodied into the MPEG and H.261/H263 motion video standards. However, some important questions remain unexplored. This book describes one possible alternative to these standards that has superior compression characteristics while requiring far less computational

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The MPEG Video Compression Standard,, and decompression of motion video. MPEG-1 [IS92b] is a standard supporting compression of image resolutions of approximately 352×288 at 30 fps into a data stream of 1.5 Mbps. This data rate is suitable for pressing onto CD-ROM. The MPEG-2 standard [IS93b] supports compression of broadcast televisi

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Discrete Cosine Transform,nd white images, or more planes for color images. We model the signal being sampled (a sequence of pixel values forming a row, column, or time-varying sequence) as a random variable with a mean of zero. The probability distribution, shown in Figure 5.1, of pixel x. given the value of pixel x. has be

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VLSI Architectures for the XYZ Video Codec,in MOPS (million operations per second) or GOPS (giga operations per second). When designing a new video codec, the first step is to estimate its complexity [BK95, PDG95, F+95, GGV92]. For example, Table 8.1, adapted from [BK95], estimates MOPS (Million Operations Per Second) requirements for H.261

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Conclusion, are comparable to other algorithms capable of high compression ratios. The XYZ encoder complexity is significantly lower than the complexity of the H.261/H/263 and MPEG algorithms (2.5 to 5 times), due to the fact that no motion estimation is necessary. On the other hand, the XYZ decoder complexity