An underwater image enhancement method based on fish retinal mechanism

Abstract

The invention discloses an underwater image enhancement method based on the fish retina mechanism. The method of the invention simulates the feedback relationship between the fish retina horizontal cells and the cone cells to remove the color cast of the underwater image, and simulates the fish Center-periphery antagonism of retinal bipolar cells to deblur underwater images. During the whole simulation process, the structure of bipolar cells inhibited by the horizontal cell side of the fish retina was simulated to design the double Gaussian difference filter of the receptive field of bipolar cells; at the same time, the sigmoid curve was used to simulate the continuous release of dopamine regulation by reticulum cells in the dark The activities of horizontal cells make the processed image more in line with the visual mechanism of fish; finally, gamma transformation is used to simulate the nonlinear processing of brightness information by amacrine cells, and constitute the central input of color bipolar cells.

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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