Underwater Image Enhancement Based on Background Light Estimation and Color Correction
摘要
To solve the problem of image degradation and color attenuation in underwater imaging,this paper proposes an image enhancement algorithm based on global background light estimation and color correction.The similarity between fog image and underwater image is used to improve the algorithm of fog removal in air.When estimating the global background light of the image,the rectangular template is selected to calculate the color saturation variance in image blocks,and the region with the minimum variance is selected as the estimated image of background light.To address the problem that the original background light estimation algorithm will make the image whiter than it should be,the minimum filtering is implemented.Also,the Retinex algorithm is used to correct the color of <i>R</i> channel of the image and then other channel graphs are obtained by combining the color attenuation coefficient ratio of each color channel.Experimental results show that this algorithm can effectively remove the turbidity of underwater images improve the color deviation of images,and significantly improve the clarity of images.