This paper mainly discusses the underwater fog technology, and mainly uses some image evaluation algorithms. Compared with other image processing algorithms, it improves the running speed of the algorithm. In short, the underwater image denoising and contrast after processing are better than the traditional image polarization defogging algorithm. The experiment specifically uses the split focus plane polarization imaging system to collect polarization pictures from multiple angles in multiple underwater scenes, and calculate its polarization stokes vector, calculate the polarization information of the scene through the stokes vector, use the general light source and linear polarization light source to illuminate the diffuse reflection and specular reflection targets respectively, compare the polarization information of different scenes, and get that the polarization information distribution of the background and target of the scene using polarization light source is clearer than that of the general light source. Then, a stokes polarization defogging algorithm is proposed. The polarization degree information calculated by stokes vector is compared with the transmission information obtained by the dark channel prior algorithm. It is found that under the condition of using polarized light source and uniform illumination, the transmission of scene can be predicted by DOP (Degree of polarization) calculated by stokes vector and used for image defogging, then some image evaluation algorithms are used to compare it with other image processing algorithms, which improves the running speed of the algorithm. The denoising and contrast of the underwater image after processing are better than the traditional image polarization defogging algorithm.
To solve the problem of blurred edges in some color images, a color image enhancement algorithm based on edge extraction is proposed. This algorithm is carried out in YUV space. The improved Laplace operator is used to extract image edge, which improves the clarity of edge while preserving image color. In addition, this algorithm can also improve the edge clarity of blurred and noisy images.
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