Sea Cucumber Image Dehazing Method by Fusion of Retinex and Dark Channel - Computer Vision Research Group（计算机视觉实验室）

This paper proposes a method based on the prior fusion of Retinex and dark channel to enhance the defogging of underwater sea cucumber images. Firstly, the original RGB image is pre-processed by dark channel prior, and then the reflection property of the image is preserved by weighted average of pixels in the image. Then, the original image is convolved with a Gaussian template to generate a high-frequency enhanced image. Finally, the brightness and saturation of the image are enhanced by changing the values of S and V in the HSV image. The experimental results are represented by four evaluation indicators such as the MSE. By processing images of sea cucumber, we obtained MSE, ENL, EI, and SNR values of 1.9782, 14.4049, 6.9586, and 14.9172, respectively. Compared with other methods, the image processed by our method has better performance in evaluating indicators. It shows that our method shows great performance in the defogging and enhancement of underwater sea cucumber images.