Articles

Multiscale video compression using adaptive finite-state vector quantization

[+] Author Affiliations
Heesung Kwon

State University of New York at Buffalo, Department of Electrical and Computer Engineering, Amherst, New York?14220

Mahesh Venkatraman

State University of New York at Buffalo, Department of Electrical and Computer Engineering, Amherst, New York?14220

Nasser M. Nasrabadi

U.S. Army Research Laboratory, Department of the Army, Adelphi, Maryland?20783-1197

J. Electron. Imaging. 7(4), 725-739 (Oct 01, 1998). doi:10.1117/1.482660
History: Received Apr. 14, 1998; Revised June 12, 1998; Accepted July 15, 1998
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Abstract

We investigate the use of vector quantizers (VQs) with memory to encode image sequences. A multiscale video coding technique using adaptive finite-state vector quantization (FSVQ) is presented. In this technique, a small codebook (subcodebook) is generated for each input vector from a much larger codebook (supercodebook) by the selection (through a reordering procedure) of a set of appropriate codevectors that is the best representative of the input vector. Therefore, the subcodebook dynamically adapts to the characteristics of the motion-compensated frame difference signal. Several reordering procedures are introduced, and their performance is evaluated. In adaptive FSVQ, two different methods, predefined thresholding and rate-distortion cost optimization, are used to decide between the supercodebook and subcodebook for encoding a given input vector. A cache-based vector quantizer, a form of adaptive FSVQ, is also presented for very-low-bit-rate video coding. An efficient bit-allocation strategy using quadtree decomposition is used with the cache-based VQ to compress the video signal. The proposed video codec outperforms H.263 in terms of the peak signal-to-noise ratio and perceptual quality at very low bit rates, ranging from 5 to 20 kbps. The picture quality of the proposed video codec is a significant improvement over previous codecs, in terms of annoying distortions (blocking artifacts and mosquito noises), and is comparable to that of recently developed wavelet-based video codecs. This similarity in picture quality can be explained by the fact that the proposed video codec uses multiscale segmentation and subsequent variable-rate coding, which are conceptually similar to wavelet-based coding techniques. The simplicity of the encoder and decoder of the proposed codec makes it more suitable than wavelet-based coding for real-time, very-low-bit-rate video applications. © 1998 SPIE and IS&T.

© 1998 SPIE and IS&T

Citation

Heesung Kwon ; Mahesh Venkatraman and Nasser M. Nasrabadi
"Multiscale video compression using adaptive finite-state vector quantization", J. Electron. Imaging. 7(4), 725-739 (Oct 01, 1998). ; http://dx.doi.org/10.1117/1.482660


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