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Adaptive-search tree-structured residual vector quantization

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3 Author(s)
Peel, C.B. ; Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA ; Xuegong Liu ; Budge, S.E.

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

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Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on  (Volume:6 )

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