In this paper, the basic theory of geometric active contour model was studied, for the degradation problems of low contrast, fuzzy and color distortion of underwater image data. Combined with the character of underwater image the adaptive GACV image segmentation algorithm was improved, new weighting function was designed, the numerical realization of the model has improved, and a mathematical model of underwater image segmentation based on the improved adaptive GACV image segmentation algorithm was established, and the underwater images were emulated. The simulation results showed that the algorithm fully segmented underwater images with low contrast and fuzzy features. Especially the underwater fuzzy image segmentation was better, which provides a reference for underwater image segmentation research.

The paper aimed at improving the problem of color distortion, blur and underexposure, which caused by absorption of water and light scattering in the underwater environment, and uneven light caused by artificial illumination in the deep sea. According to the ideal of removing the color distortion after the image blurring removal [1], a novel method of image enhancement has propose, combining multi-scale retinex (MSR) and color correction algorithm based on color histogram quantization. The color correction algorithm based on color channel histogram was used to adjust the image to improve problems of the low contrast, color attenuation, overall fuzzy, unclear details and so on. The experimental results showed that the proposed method can effectively reduce the influence of color distortion and highlight the image details, so that the underwater color image has better visual effect.