The gray levels of gastric sonogram images are usually concentrated at the
zero end of the spectrum, making the image too low in contrast and too dark
for the naked eye. Though histogram equalization can enhance the contrast
by redistributing the gray levels, it has the drawback that it reduces the
information in the processed image. In this paper, a wavelet-based enhancem
ent algorithm post-processor is used to further enhance the image and compe
nsate for the information loss during histogram equalization. Experimental
results show that the wavelet-based enhancement algorithm can enhance the c
ontrast and significantly increase the informational entropy of the image.
Because the combination of the histogram equalization and wavelet approach
can dramatically increase the contrast and maintain information rate in gas
tric sonograms, it has the potential to improve clinical diagnosis and rese
arch. (C) 2000 Elsevier Science Ltd. All rights reserved.