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      • Department of Electrical and Electronics Engineering
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      Near-lossless image compression techniques

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      Author
      Ansari, R.
      Memon, N.
      Ceran, E.
      Date
      1998
      Source Title
      Journal of Electronic Imaging
      Print ISSN
      1017-9909
      Publisher
      S P I E - International Society for Optical Engineering
      Volume
      7
      Issue
      3
      Pages
      486 - 494
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      Predictive and multiresolution techniques for near- lossless image compression based on the criterion of maximum allowable deviation of pixel values are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is described. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG-LS, are provided. Application of lossless coding based on reversible transforms in conjunction with prequantization is shown to be inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multiresolution 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. Results show that this lossy plus near-lossless technique yields compression ratios close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream. © 1998 SPIE and IS&T.
      Keywords
      Computer simulation
      Fits and tolerances
      Image coding
      Image quality
      Image reconstruction
      Standards
      Joint picture experts group (JPEG) standards
      Near lossless image compression methods
      Image compression
      Permalink
      http://hdl.handle.net/11693/25443
      Published Version (Please cite this version)
      https://doi.org/10.1117/1.482591
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      • Department of Electrical and Electronics Engineering 3524
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