Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution

This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels. To enhance video, the proposed image-enhancement method uses temporal information regarding the differences between each frame to reduce computational complexity. Experimental results demonstrate that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods.

I. Introduction

Contrast enhancement plays an important role in the improvement of visual quality for computer vision, pattern recognition, and the processing of digital images. Poor contrast in digital video or images can result from many circumstances, including lack of operator expertise and inadequacy of the image capture device. Unfavorable environmental conditions in the captured scene, such as the presence of clouds, lack of sunlight or indoor lighting, and other conditions, might also lead to reduced contrast quality [1]. Essentially, if the overall luminance is insufficient, then the details of the image or video features will be obscured.