Low Light Image Contrast Enhancement using Blending of Histogram Equalization Based Methods BBHE and BPHEME

Abstract

Image contrast is the difference between the brightness and colors of a part of an image compared to its objects around. The contrast enhancement means increasing the original input brightness values. Images captured in low-light environments suffer from inferior visibility caused by low contrast. It is said that Histogram equalization is the foundation of image contrast enhancement and is used even in new contrast enhancement methods. Even though Histogram Equalization (HE) is primitive, it is effective. HE increases the brightness of the output image significantly, which is often undesirable. There are various enhanced versions of histogram equalization methods to improve image contrast are proposed to overcome the brightness preservation and image details preservation challenge. This paper focuses on studying different popular and approved HE methods and experimental studies based on the image, PSNR - peak signal to noise ratio, BRISQUE - Blind / Reference less Image Spatial Quality Evaluator, and Entropy. Results from the above study direct the goal towards the Image fusion of the two selected methods, which gives improved results on the preservation of brightness and contrast enhancement of the original image.