A near-lossless trellis-searched predictive image compression system
@article{Moayeri1996ANT,
title={A near-lossless trellis-searched predictive image compression system},
author={Nader Moayeri},
journal={Proceedings of 3rd IEEE International Conference on Image Processing},
year={1996},
volume={2},
pages={93-96 vol.2},
url={https://api.semanticscholar.org/CorpusID:42883060}
}This paper presents a near-lossless image compression system where the coded image is within some prespecified maximum error of the original image at each and every pixel. The system is predictive…
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7 References
Near-lossless image compression: minimum-entropy, constrained-error DPCM
- 1995
Computer Science
A near-lossless image compression scheme with a mechanism incorporated to minimize the entropy of the quantized prediction error sequence and an algorithm that produces minimum entropy conditioned on the contexts is presented.
Near-lossless compression of medical images through entropy-coded DPCM
- 1994
Computer Science, Medicine
Experiments involving several MR and US images show that the entropy-coded DPCM method can provide compression in the range from 4 to 10 with a peak SNR of about 50 dB for 8-bit medical images, and a comparison with the JPEG standard reveals that it can provide about 7 to 8 dB higher SNR for the same compression performance.
Reversible compression of HDTV images using median adaptive prediction and arithmetic coding
- 1990
Computer Science, Engineering
Methods of compressing HDTV (high-definition television) image sequences are investigated. Best results are achieved by a new combination of median adaptive intraframe prediction and arithmetic…