Image contrast enhancement based on a local standard deviation model

Dah Chung Chang*, Wen-Rong Wu

*Corresponding author for this work

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt's Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm.

Original languageEnglish
Pages1826-1830
Number of pages5
DOIs
StatePublished - 1 Dec 1996
EventProceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3) - Anaheim, CA, USA
Duration: 2 Nov 19969 Nov 1996

Conference

ConferenceProceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3)
CityAnaheim, CA, USA
Period2/11/969/11/96

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    Chang, D. C., & Wu, W-R. (1996). Image contrast enhancement based on a local standard deviation model. 1826-1830. Paper presented at Proceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3), Anaheim, CA, USA, . https://doi.org/10.1109/NSSMIC.1996.587984