Image contrast enhancement based on a local standard deviation model

Dah Chung Chang; Wen-Rong Wu

doi:10.1109/NSSMIC.1996.587984

Image contrast enhancement based on a local standard deviation model

Dah Chung Chang^*, Wen-Rong Wu

^*Corresponding author for this work

Department of Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

5 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 language	English
Pages	1826-1830
Number of pages	5
DOIs	https://doi.org/10.1109/NSSMIC.1996.587984
State	Published - 2 Nov 1996
Event	Proceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3) - Anaheim, CA, USA Duration: 2 Nov 1996 → 9 Nov 1996

Conference

Conference	Proceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3)
City	Anaheim, CA, USA
Period	2/11/96 → 9/11/96

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10.1109/NSSMIC.1996.587984

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title = "Image contrast enhancement based on a local standard deviation model",

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.",

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AU - Wu, Wen-Rong

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AB - 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.

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T2 - Proceedings of the 1996 IEEE Nuclear Science Symposium. Part 1 (of 3)

Y2 - 2 November 1996 through 9 November 1996

ER -

Image contrast enhancement based on a local standard deviation model

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