ADAPTIVE NONLINEAR IMAGE ENHANCEMENT of GAUSSIAN DEGRADED IMAGES

Rahul Gowda, Shalin M. Mehta, Yue Yang, Baoxin Li

Research output: Contribution to journalArticle

Abstract

An adaptive technique for nonlinear image enhancement using Gabor filters is proposed. A set of Gabor filters are employed to extract high-pass components from the blurred image and these components are then nonlinearly processed before adding back to the input image for enhancement. Further, we propose a novel method for fast blur estimation and we establish an empirical relationship between the estimated blur and the optimal Gabor filter parameters, resulting in an enhancement system that is adaptive to the degree of blur in the input image. Extensive evaluation, including both PSNR-based objective evaluation and subjective psychophysical tests, confirms the advantages of the proposed approach over existing state-of-the-art methods. This enhancement approach is especially targeted at digital television applications where image blur is present due to various reasons like compression and resolution up-conversion.

Original languageEnglish (US)
Pages (from-to)365-393
Number of pages29
JournalInternational Journal of Image and Graphics
Volume10
Issue number3
DOIs
StatePublished - Jul 1 2010

Keywords

  • blur estimation
  • Gabor
  • HDTV
  • Image enhancement

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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