1 October 2006 Scalable near-lossless image coding
Author Affiliations +
Abstract
In near-lossless image coding, each reconstructed pixel of the decoded image differs from the corresponding one in the original image by not more than a prespecified value. Such schemes are mainly based on predictive coding techniques, which are not capable of quality or resolution-wise scalable decoding. Lossless image coding with scalable decoding is mainly based on transforms that map integers to integers using lifting factorization. In this work, the near-lossless quantization is incorporated into lifting to develop a wavelet-based near-lossless image coding scheme that supports scalability. The proposed technique, which performs online quantization, eliminates the inefficiencies of prequantization-based near-lossless coding and the difficulty in wavelet domain near-lossless quantizing. Two online near-lossless quantization techniques based on 1-D and 2-D transforms are presented. The algorithms outperform the prequantization-based near-lossless image coding in both bit rate and root mean square (rms) error performances, resulting in both subjectively and objectively superior performance in scalable decoding. The 2-D online scheme results in comparable performance with JPEG-LS, which is a nonscalable coding technique. Using these novel schemes enables scalable decoding of near-lossless coded images at the expense of a small increase in bit rates compared to those achieved using JPEG-LS.
©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Charith K. Abhayaratne "Scalable near-lossless image coding," Journal of Electronic Imaging 15(4), 043008 (1 October 2006). https://doi.org/10.1117/1.2360694
Published: 1 October 2006
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Image compression

Transform theory

Quantization

Wavelet transforms

Image processing

Image quality

Gold

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