ncoders. Obviously the complexity of the decoder is much sim- Interframe redundancy can be simply modeled as static pler than the encoder. The size of the codebook dictates backgrounds and moving foregrounds to illustrate the both the coding efficiency and reconstruction quality. potential temporal compression that can be realized. The raw bit rate of a vector quantizer is, Over a short period of time, image sequences can be described as a static background with moving objects in bitratevq = (7.4.10) the foreground. If the background does not change between two frames, their difference is zero, and the two background frames can essentially be encoded as one. where log2 m is the number of bits required to transmit Therefore the compression ratio increase is proportional the index i of the codebook vector X. The codebook to two times the spatial compression achieved in the first construction includes two important issues that are frame. In general, unchanging or static backgrounds can pertinent to the performance of the video coder. The set realize additive coding gains, i.e., of vectors that are included in the codebook determine the bit rate and distortion characteristics of the Static Back ground Coding Gain a N (Spatial reconstructed image sequence. The codebook size and Compression Ratio of Background Frame) (7.4.11) structure determines the search complexity to find the minimum error solution for Eq. (7.4.9). Two important where N is the number of static background frames being VQ codebook designs are the Linde-Buzo-Gray (LBG) encoded. Static backgrounds occupy a great deal of the Video compression CHAPTER 7.4 image area, and are typical of both natural and animated vertical direction of the image block, i and j are the pixel image sequences. Some variation in the background indices within the image block, and m and n are the in- always occurs due to random and systematic fluctuations. dices of the search neighborhood in the horizontal and This tends to reduce the achievable background coding vertical directi