DocumentCode
1622868
Title
Image contrast enhancement based on a local standard deviation model
Author
Chang, Dah-chung ; Wu, Wen-Rong
Author_Institution
Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume
3
fYear
1996
Firstpage
1826
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. Here, a new gain is developed based on Hunt´s (1976) 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. The authors have applied the new ACE algorithm to chest X-ray images and the simulations show the effectiveness of the proposed algorithm
Keywords
adaptive signal processing; diagnostic radiography; image enhancement; medical image processing; modelling; Hunt´s Gaussian image model; adaptive contrast enhancement algorithm; chest X-ray images; image contrast enhancement; image high frequency components; local standard deviation model; medical diagnostic imaging; noise overenhancement; nonlinear function; ringing artifact; Adaptive equalizers; Biomedical equipment; Communication standards; Frequency; Histograms; Image enhancement; Medical services; Medical simulation; Noise reduction; X-ray imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Nuclear Science Symposium, 1996. Conference Record., 1996 IEEE
Conference_Location
Anaheim, CA
ISSN
1082-3654
Print_ISBN
0-7803-3534-1
Type
conf
DOI
10.1109/NSSMIC.1996.587984
Filename
587984
Link To Document