30 January 2003 Decomposing bit planes to reduce compression requirement for lossless channels
Author Affiliations +
Abstract
Segmentation of images to bit planes is one of the techniques for scalable image compression. Assuming our source image to be from a uniform quantizer, we categorize its bit planes on the basis of their significance, into two groups called MSB-planes and LSB-planes. The MSB planes contain low-entropy structural information, whereas LSB planes contain high entropy texture information. Due to the different nature of information and entropy of the two groups, they can be coded and reconstructed by different algorithms. The structural nature of MSB planes, make them more compressible at entropy coding stage, whereas the low significance of LSB-planes can be exploited against their high entropy. We realize the later by subsampling of LSB-planes, which in turn requires attention to the close coupling of MSB and LSB planes at the reconstruction stage. We introduce an estimation algorithm for the LSB planes. The reconstructed images are found to be perceptually comparable to the original images. Quantitative comparison also shows significant coding gain in terms of SNR vs. bit rate.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Asif Hayat, Asif Hayat, Tae-Sun Choi, Tae-Sun Choi, } "Decomposing bit planes to reduce compression requirement for lossless channels", Proc. SPIE 4793, Mathematics of Data/Image Coding, Compression, and Encryption V, with Applications, (30 January 2003); doi: 10.1117/12.451252; https://doi.org/10.1117/12.451252
PROCEEDINGS
7 PAGES


SHARE
RELATED CONTENT

Finite-state residual vector quantizer for image coding
Proceedings of SPIE (October 22 1993)
Block adaptive classified vector quantization
Proceedings of SPIE (April 17 1995)
Fractal transform coding of color images
Proceedings of SPIE (September 16 1994)
Image coding methods and their assessment
Proceedings of SPIE (October 01 1992)
Interpolative Adaptive Vector Quantization
Proceedings of SPIE (July 18 1988)

Back to Top