Title :
Modulus quantization for matching-pursuit video coding
Author :
Neff, Ralph ; Zakhor, Avideh
Author_Institution :
Video & Image Process. Lab., California Univ., Berkeley, CA, USA
fDate :
9/1/2000 12:00:00 AM
Abstract :
Overcomplete signal decomposition using matching pursuits has been shown to be an efficient technique for coding motion-residual images in a hybrid video coder. Unlike orthogonal decomposition, matching pursuit uses an in-the-loop modulus quantizer which must be specified before coding begins. This complicates the quantizer design, since the optimal quantizer depends on the statistics of the matching-pursuit coefficients which in turn depend on the in loop quantizer actually used. In this paper, we address the modulus quantizer design issue, specifically developing frame-adaptive quantization schemes for the matching-pursuit video coder. Adaptive dead-zone subtraction is shown to reduce the information content of the modulus source, and a uniform threshhold quantizer is shown to be optimal for the resulting source. Practical two-pass and one-pass algorithms are developed to jointly determine the quantizer parameters and the number of coded basis functions in order to minimize coding distortion for a given rate. The compromise one-pass scheme performs nearly as well as the full two-pass algorithm, but with the same complexity as a fixed-quantizer design. The adaptive schemes are shown to outperform the fixed quantizer used in earlier works, especially at high bit rates, where the gain is as high as 1.7 dB
Keywords :
adaptive codes; quantisation (signal); video coding; 1.7 dB; adaptive dead-zone subtraction; coded basis functions; coding distortion; complexity; frame-adaptive quantization schemes; hybrid video coder; in-the-loop modulus quantizer; information content; matching-pursuit video coding; modulus quantization; motion-residual images; one-pass algorithms; overcomplete signal decomposition; two-pass algorithms; uniform threshhold quantizer; Bit rate; Dictionaries; Discrete cosine transforms; Image coding; Image reconstruction; Matching pursuit algorithms; PSNR; Quantization; Signal resolution; Video coding;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on