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A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
Electrical and Computer Engineering Faculty Publications
This paper presents a novel VQ structure which provides very good quality encoding for video sequences and exploits the computational savings gained from a fast-search algorithm. It uses an adaptive-search, variable-length encoding method which allows for very fast matching of a wide range of transmission rates. Both the encoding quality and the computational benefits from the fast-search algorithm are presented. Simulations show that full-search tree residual VQ (FTRVQ) can provide up to 3 dB improvement over a similar RVQ encoder on video sequences.
Adaptive-Rate Tree-Structured Residual Vector Quantization, Christian B. Peel, X. Liu, Scott E. Budge
Adaptive-Rate Tree-Structured Residual Vector Quantization, Christian B. Peel, X. Liu, Scott E. Budge
Electrical and Computer Engineering Faculty Publications
Full-search vector quantization (VQ) provides optimal results only with high memory and computational cost. We describe the computational and memory requirements of tree-structured VQ, residual VQ (RVQ), and tree-structured RVQ. We present multiple-rate, adaptive-search implementations of these VQ structures, and simulation results with video sequences. Tree-structured RVQ provides up to 1.5 db PSNR quality improvements over RVQ, as well as significant perceptual improvement. These algorithms maintain many of the benefits of full-search VQ, while providing trade-offs between computational, storage, and performance requirements.
Rate-Distortion Adaptive Vector Quantization For Wavelet Imagecoding, Qun Gu, Scott E. Budge
Rate-Distortion Adaptive Vector Quantization For Wavelet Imagecoding, Qun Gu, Scott E. Budge
Electrical and Computer Engineering Faculty Publications
We propose a wavelet image coding scheme using rate-distortion adaptive tree-structured residual vector quantization. Wavelet transform coefficient coding is based on the pyramid hierarchy (zero-tree), but rather than determining the zero-tree relation from the coarsest subband to the finest by hard thresholding, the prediction in our scheme is achieved by rate-distortion optimization with adaptive vector quantization on the wavelet coefficients from the finest subband to the coarsest. The proposed method involves only integer operations and can be implemented with very low computational complexity. The preliminary experiments have shown some encouraging results: a PSNR of 30.93 dB is obtained at 0.174 …