Quantifying color image distortions based on adaptive spatio-chromatic signal decompositions

Umesh Rajashekar, Zhou Wang, Eero P. Simoncelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe a framework for quantifying color image distortion based on an adaptive signal decomposition. Specifically, local blocks of the image error are decomposed using a set of spatiochromatic basis functions that are adapted to the spatial and color structure of the original image. The adaptive functions are chosen to isolate specific distortions such as luminance, hue, and saturation changes. These adaptive basis functions are used to augment a generic orthonormal basis, and the overall distortion is computed from the weighted sum of the coefficients of the resulting overcomplete decomposition, with smaller weights chosen for the adaptive terms. A set of preliminary experiments show that the proposed distortion measure is consistent with human perception of color images subjected to a variety of different common distortions. The framework may be easily extended to include any form of continuous spatio-chromatic distortion.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages2213-2216
Number of pages4
ISBN (Print)9781424456543
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: Nov 7 2009Nov 10 2009

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2009 IEEE International Conference on Image Processing, ICIP 2009
Country/TerritoryEgypt
CityCairo
Period11/7/0911/10/09

Keywords

  • Adaptive signal decomposition
  • Color image quality assessment

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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