Image enhancement using Exposure based Sub Image Histogram Equalization

• Exposure based Sub Image HE proved to be very effective for contrast enhancement.
• The histogram clipping is combined with HE to provide control on over enhancement.
• This method proved to be very effective for enhancing under exposed images.
• The entropy measures of the ESIHE method outperform other HE based methods.

This paper presents a novel Exposure based Sub-Image Histogram Equalization (ESIHE) method for contrast enhancement for low exposure gray scale image. Exposure thresholds are computed to divide the original image into sub-images of different intensity levels. The histogram is also clipped using a threshold value as an average number of gray level occurrences to control enhancement rate. The individual histogram of sub images is equalized independently and finally all sub images are integrated into one complete image for analysis. The simulation results show that ESIHE outperforms other conventional Histogram Equalization (HE) methods in terms of image visual quality, entropy preservation and better contrast enhancement.