Wavelet-based histogram equalization enhancement of gastric sonogram images.
Academic Article
Overview
abstract
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 enhancement algorithm post-processor is used to further enhance the image and compensate for the information loss during histogram equalization. Experimental results show that the wavelet-based enhancement algorithm can enhance the contrast 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 gastric sonograms, it has the potential to improve clinical diagnosis and research.
