Optimal Bezier Curve Modification Function for Contrast Degraded Images

Contrast enhancement plays a vital role in image processing and computer vision applications. However, the existing work inevitably introduces some unwanted artifacts and often fails in revealing image details when enhancing the invisible images. This article presents a novel Bezier curve modification scheme to improve the visual quality of contrast degraded imperceptible images. First, a salp swarm algorithm is incorporated to compute an optimal threshold value using weighted cumulative distribution function for adjusting the transformation in bright and dark areas separately. Then, an optimized Bezier curve uses a novel regularization parameter to improve the fine details of bright and dark regions, respectively. The experiential results are provided to demonstrate that the proposed method yields better quantitative results compared with the existing methods. Extensive experiments on different data sets demonstrate that the proposed method produces an enhanced image with superior visual quality for all five levels of contrast distorted images.