1998Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Near-lossless image compression techniques

Rashid Ansari, Ersan Ceran, Nasir Memon

Open publisher page 3 citations

Abstract

Methods of near-lossless image compression based on the criterion of maximum allowable deviation of pixel values are described in this paper. Predictive and multi resolution techniques for performing near-lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is descried. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG- LS, are provided. It is shown that the application of lossless coding based on reversible transforms in conjunction with pre-quantization is inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multi-resolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Simulation results show that this lossy plus-lossless technique yields compression ratios very close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream.

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What this paper is about

Methods of near-lossless image compression based on the criterion of maximum allowable deviation of pixel values are described in this paper. Predictive and multi resolution techniques for performing near-lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is descried. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG- LS, are provided. It is shown that the application of lossless coding based on reversible transforms in conjunction with pre-quantization is inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multi-resolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Simulation results show that this lossy plus-lossless technique yields compression ratios very close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream.

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Available abstract

Methods of near-lossless image compression based on the criterion of maximum allowable deviation of pixel values are described in this paper. Predictive and multi resolution techniques for performing near-lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless compression are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is descried. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG- LS, are provided. It is shown that the application of lossless coding based on reversible transforms in conjunction with pre-quantization is inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multi-resolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Simulation results show that this lossy plus-lossless technique yields compression ratios very close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream.

Key concepts: Lossless compression, Lossy compression, Lossless JPEG, Image compression, Computer science, Data compression, Data compression ratio, Algorithm

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