Image enhancement based on equal area dualistic sub-image histogram equalization method

TLDR

Histogram equalization is a simple and effective image enhancing technique, but it can significantly alter image luminance, limiting its use in video systems. This paper proposes equal area dualistic sub‑image histogram equalization to address this luminance distortion. The method decomposes the image into two equal‑area sub‑images based on the original probability density function, equalizes each sub‑image separately, and then recombines them. Simulations show the algorithm enhances image detail while preserving luminance, enabling direct application in video systems.

Abstract

Histogram equalization is a simple and effective image enhancing technique. But in some conditions, the luminance of an image may be changed significantly after the equalizing process, this is why it has never been utilized in a video system in the past. A novel histogram equalization technique, equal area dualistic sub-image histogram equalization, is put forward in this paper. First, the image is decomposed into two equal area sub-images based on its original probability density function. Then the two sub-images are equalized respectively. Finally, we obtain the results after the processed sub-images are composed into one image. The simulation results indicate that the algorithm can not only enhance the image information effectively but also preserve the original image luminance well enough to make it possible to be used in a video system directly.