Adaptive perceptual block compressive sensing for image compression

Jin Xu, Yuansong Qiao, Zhizhong Fu

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Because the perceptual compressive sensing framework can achieve a much better performance than the legacy compressive sensing framework, it is very promising for the compressive sensing based image compression system. In this paper, we propose an innovative adaptive perceptual block compressive sensing scheme. Firstly, a new block-based statistical metric which can more appropriately measure each block's sparsity and perceptual sensibility is devised. Then, the approximated theoretical minimum measurement number for each block is derived from the new block-based metric and used as weight for adaptive measurements allocation. The obtained experimental results show that our scheme can significantly enhance both objective and subjective performance of a perceptual compressive sensing framework.

Original languageEnglish
Pages (from-to)1702-1706
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE99D
Issue number6
DOIs
Publication statusPublished - Jun 2016

Keywords

  • Adaptive Measurements Allocation
  • Discrete Cosine Transform
  • Image Compression
  • Perceptual Compressive Sensing

Fingerprint

Dive into the research topics of 'Adaptive perceptual block compressive sensing for image compression'. Together they form a unique fingerprint.

Cite this