Research on the picture hierarchy enhancement technique based on probability distribution in oil paintings

With the rapid development of computer vision technology, image enhancement technology involves an increasingly wide range of research content.At the current stage, picture hierarchy enhancement technology is a research hotspot in the field of image enhancement.This paper proposes an oil painting image enhancement network based on positive probability distribution guidance.The multidimensional spatial information of the samples is obtained through the multibranch information extraction architecture in the network structure, and the probability distribution estimation module estimates the probability distribution through the obtained multidimensional spatial information.In addition, a new image enhancement method based on the RGB color balance method is proposed, which combines the multi-scale Retinex enhancement algorithm with color recovery and the RGB, Lab color space histogram adaptive stretching algorithm, to further improve the effect of oil painting image display.The experimental results show that the method has a better image color bias correction effect compared with the existing techniques.In terms of subjective evaluation, the average subjective score of this paper's method in three different aesthetic levels reaches 9.15, obtaining a high evaluation.The samples enhanced based on this paper's algorithm all obtained high aesthetic index scores, indicating that the oil paintings under this paper's algorithm are in line with the public aesthetics, which is of great significance to the work of oil painting artists.