Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting
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@Article{JICS-4-211,
author = {PongsakLasang , Chang-su Kim and WuttipongKumwilaisak},
title = {Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {4},
number = {3},
pages = {211--223},
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.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22747.html}
}
TY - JOUR
T1 - Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting
AU - PongsakLasang , Chang-su Kim and WuttipongKumwilaisak
JO - Journal of Information and Computing Science
VL - 3
SP - 211
EP - 223
PY - 2024
DA - 2024/01
SN - 4
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22747.html
KW - Multi-view image coding, rate-complexity scalability, wavelet lifting, disparity-compensation,
image feature matching.
AB - 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.
PongsakLasang , Chang-su Kim and WuttipongKumwilaisak. (2024). Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting.
Journal of Information and Computing Science. 4 (3).
211-223.
doi:
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