Image quality assessment: From error visibility to structural similarity

Zhou Wang, Alan Conrad Bovik, Hamid Rahim Sheikh, Eero P. Simoncelli

Research output: Contribution to journalArticlepeer-review

Abstract

Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a Structural Similarity Index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000.

Original languageEnglish (US)
Pages (from-to)600-612
Number of pages13
JournalIEEE Transactions on Image Processing
Volume13
Issue number4
DOIs
StatePublished - Apr 2004

Keywords

  • Error sensitivity
  • Human visual system (HVS)
  • Image coding
  • Image quality assessment
  • JPEG
  • JPEG2000
  • Perceptual quality
  • Structural information
  • Structural similarity (SSIM)

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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