Multi-scale structural similarity for image quality assessment

Zhou Wang, Eero P. Simoncelli, Alan C. Bovik

Research output: Contribution to journalConference articlepeer-review


The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a good approximation to perceived image quality. This paper proposes a multi-scale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions. We develop an image synthesis method to calibrate the parameters that define the relative importance of different scales. Experimental comparisons demonstrate the effectiveness of the proposed method.

Original languageEnglish (US)
Pages (from-to)1398-1402
Number of pages5
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
StatePublished - 2003
EventConference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 9 2003Nov 12 2003

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications


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