An Enhancement of Underwater Images Based on Contrast Restricted Adaptive Histogram Equalization for Image Enhancement

Scattering of light and absorption color affects the images of underwater. Due to this visibility and contrast on underwater, images are reduced. Dark channel prior is used typically for restoration. Poor resolution and contrast are exhibited by the images of underwater due to scattering of light and absorption of it in the environment of underwater. Color is caused by this situation. Due to this, it is difficult to analyze the image of underwater in an efficient manner for the object identification. In this paper, adaptive histogram equalization (AHE)-based new underwater image enhancement technique is proposed to get enhanced results. In the formula of gray-level mapping, parameter β is introduced by AHE algorithm. In new histogram, the spacing between two adjacent gray levels is adjusted adaptively to take target function as information entropy. In image, excessive local area and gray pixel merger are avoided by this. Settings of camera will not affect the performance of AHE as shown by validation and various image processing application’s accuracy are enhanced. The results of image enhancement methods are measured using the metrics like underwater image quality measure (UIQM), underwater color image quality evaluation (UCIQE), and patch-based contrast quality index (PCQI).