A star map compression algorithm

Chen Wei Deng*, Bao Jun Zhao, Hai Yan Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

There exist a large amount of redundant information in the smooth areas of a star map. Based on this characteristic, a star map compression algorithm is proposed relying on target object. This algorithm divides a star map into two sets of which, one is the smooth background and the other the complicated target object. The former areas can be coded with less data quantity when the latter areas are being coded, wavelet decomposition is applied to remove the relativity among pixels. Then the coefficients can be coded efficiently through energy clustering. Experimental results showed that the proposed algorithm achieved good visual quality and the peak signal-to-noise ratio (PSNR) is excellent.

Original languageEnglish
Pages (from-to)1096-1100
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume28
Issue number12
Publication statusPublished - Dec 2008

Keywords

  • Discrete wavelet transform
  • Image compression
  • Object segmentation
  • Quadtree classification
  • Run-length coding

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