Weighted average multi segment histogram equalization for brightness preserving contrast enhancement

Histogram equalization (HE) is one of the most effective method for contrast enhancement, but it fails to preserve the mean brightness of images. To overcome such drawback, several Bi- and multi-histogram equalization methods have been proposed. Among them, Bi-HE methods may preserve the brightness, but they introduce some undesirable artifacts in the processed image. On the other hand, Multi-HE methods may not introduce undesirable artifacts in image but at the cost of either the brightness or its contrast. In this paper, we propose a weighted average multi segment HE method using Gaussian filter for contrast enhancement of natural images while preserving mean brightness. It also reduces noise present in the images. The proposed method first smooths the global histogram and decomposes it into multiple segments via optimal thresholds, and then HE is applied to each segment independently. Simulation results for several test images show that the proposed method enhances the contrast while preserving mean brightness.