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
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;
Conference_Titel :
Nuclear Science Symposium, 1996. Conference Record., 1996 IEEE
Conference_Location :
Anaheim, CA
Print_ISBN :
0-7803-3534-1
DOI :
10.1109/NSSMIC.1996.587984