Significance-linked connected component analysis for very low bit-rate wavelet video coding

Abstract

A novel hybrid wavelet video coding algorithm termed video significance-linked connected component analysis (VSLCCA) is developed for very low bit-rate applications. In the proposed VSLCCA codec, first, fine-tuned motion estimation based on the H.263 Recommendation is developed to reduce temporal redundancy, and exhaustive overlapped block motion compensation is utilized to ensure coherency in motion compensated error frames. Second, the wavelet transform is applied to each coherent motion compensated error frame to attain global energy compaction. Third, significant fields of wavelet-transformed error frames are organized and represented as significance-linked connected components so that both the within-subband clustering and the cross-scale dependency are exploited. Last, the horizontal and vertical components of motion vectors are encoded separately using adaptive arithmetic coding while significant wavelet coefficients are encoded in bit-plane order by using high order Markov source modeling and adaptive arithmetic coding. Experimental results on eight standard MPEG-4 test sequences show that for intraframe coding, on average the proposed codec exceeds H.263 and ZTE (zero-tree entropy) in peak signal-to-noise ratio by as much as 2.07 and 1.38 dB at 28 kbit/s, respectively. For entire sequence coding, VSLCCA is superior to H.263 and ZTE by 0.35 and 0.71 dB on average, respectively.