Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting
نویسندگان
چکیده
Abstract. This paper presents a novel algorithm for rate-complexity scalable multi-view image coding using an adaptive disparity-compensated (DC) wavelet lifting scheme. First, image regions of multi-view images are prioritized by counting matching points. The proposed algorithm selects either Haar, 5/3, or our proposed multiple picture reference DC wavelet lifting adaptively. The selection criterion is based on the bit budget constraint, the complexity budget constraint, and the priorities of image regions. Then, the low-pass and high-pass subbands, obtained from the DC wavelet lifting, are further decomposed by a spatial wavelet transform. The resulting wavelet coefficients are entropy encoded with the SPIHT codec. Experimental results show that the proposed algorithm provides an efficient adaptive framework for multi-view image coding.
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