Least-squares-based switching structure for lossless image coding

Lih Jen Kau*, Yuan-Pei Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Many coding methods are more efficient with some images than others. In particular, run-length coding is very useful for coding areas of little changes. Adaptive predictive coding achieves high coding efficiency for fast changing areas like edges. In this paper, we propose a switching coding scheme that will combine the advantages of both run-length and adaptive linear predictive coding. For pixels in slowly varying areas, run-length coding is used; otherwise least-squares (LS)-adaptive predictive coding is used. Instead of performing LS adaptation in a pixel-by-pixel manner, we adapt the predictor coefficients only when an edge is detected so that the computational complexity can be significantly reduced. For this, we use a simple yet effective edge detector using only causal pixels. This way, the proposed system can look ahead to determine if the coding pixel is around an edge and initiate the LS adaptation in advance to prevent the occurrence of a large prediction error. With the proposed switching structure, very good prediction results can be obtained in both slowly varying areas and pixels around boundaries. Furthermore, only causal pixels are used for estimating the coding pixels in the proposed encoder; no additional side information needs to be transmitted. Extensive experiments as well as comparisons to existing state-of-the-art predictors and coders will be given to demonstrate its usefulness.

Original languageEnglish
Pages (from-to)1529-1541
Number of pages13
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Volume54
Issue number7
DOIs
StatePublished - 1 Jul 2007

Keywords

  • Adaptive prediction
  • Context modeling
  • Edge detection
  • Entropy coding
  • Least-squares (LS) optimization
  • Lossless image coding
  • Run-length encodings

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