Underwater image enhancement method based on fish retina mechanism

Abstract

The invention discloses an underwater image enhancement method based on a fish retina mechanism. According to the method, a feedback relation between fish retina horizontal cells and cone cells is simulated to remove the color cast of an underwater image, and a center-periphery antagonistic effect of fish retina bipolar cells is simulated to remove blur of the underwater image. In the whole simulation process, a structure for suppressing the bipolar cells at the fish retina horizontal cell side is simulated so as to design a dual-Gauss difference filter of a receptive field of the bipolar cells; and meanwhile, an activity of interplexiform cells for continuously releasing Dopamine in dark to regulate the horizontal cells is simulated by using a sigmoid curve, and thus the processed image is enabled to more conform to a vision mechanism of the fish; and finally nonlinear processing of amacrine cells for brightness information is simulated by adopting gamma conversion, and central input of color bipolar cells is formed.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to a color image enhancement technology, in particular to an underwater image enhancement method based on a fish retina mechanism. Background technique [0002] With the continuous enhancement of human exploration capabilities, more and more underwater images have been widely disseminated and applied. However, due to the backscattering and forward scattering of suspended particles in the water body, the image will be blurred, and the color of the underwater image will have a blue-green cast due to the different attenuation speeds of light waves of different wavelengths after the light enters the water. Image blur and color cast will make the final underwater image not clear enough. Therefore, how to remove the influence of blur and color cast and obtain underwater images with high contrast has become a more important issue. [0003] Existing image deblurring methods are main...

AI Technical Summary

Problems solved by technology

However, they are mainly for land scenes, ignoring some characteristics of underwater images

Among them, the learning-based method is still difficult to apply to underwater image processing because there is currently no underwater image database with a standard light source; while the static method is mostly based on certain grayscale assumptions, but generally the red band of underwater images is obvious. Weaker than other bands and does not meet the grayscale assumption, so the color of the image corrected by the static method is mostly reddish. Even some improved static methods must satisfy the dark channel prior model to have a certain effect

Fish retina can solve the problem of color cast and blur at the same time, but there is no method to simulate fish retina to deal with color cast and blur at the same time

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