Abstract
In order to solve the problem of poor visual communication effect of impressionist painting colors and low accuracy of painting color enhancement by existing methods, this thesis proposes a research on the performance of impressionist painting color visual communication based on machine vision under the background of wireless network. This method can improve the vision, speed, and efficiency of communication, through the analysis of the characteristics of impressionist paintings, and determine the visual communication objects of impressionist painting colors. The process of visual communication is analyzed, and the color matching of impressionist painting is completed with the help of BP neural network algorithm. On this basis, the histogram method is used to process the image brightness of impressionist paintings, the image interpolation method is used to process the image brightness of impressionist paintings, and the image is corrected by gamma correction to complete the image performance research. The color vision communication of impressionist painting needs to correct the gray scale error of impressionist painting and enhance the color of impressionist painting. The experimental results show that the accuracy of this method for the color matching of impressionist painting images is about 98%, which has a certain degree of credibility.
Highlights
In order to solve the problem of poor visual communication effect of impressionist painting colors and low accuracy of painting color enhancement by existing methods, this thesis proposes a research on the performance of impressionist painting color visual communication based on machine vision under the background of wireless network. is method can improve the vision, speed, and efficiency of communication, through the analysis of the characteristics of impressionist paintings, and determine the visual communication objects of impressionist painting colors. e process of visual communication is analyzed, and the color matching of impressionist painting is completed with the help of BP neural network algorithm
The histogram method is used to process the image brightness of impressionist paintings, the image interpolation method is used to process the image brightness of impressionist paintings, and the image is corrected by gamma correction to complete the image performance research. e color vision communication of impressionist painting needs to correct the gray scale error of impressionist painting and enhance the color of impressionist painting. e experimental results show that the accuracy of this method for the color matching of impressionist painting images is about 98%, which has a certain degree of credibility
A low-contrast input image is decomposed into luminance and chrominance components in Lab color space, and adaptive bilateral filtering is used to estimate the illumination intensity, so as to consider the appropriate adjacent pixels according to the luminance and color values. en, the parabola-based tone mapping function is used to improve the contrast of the estimated illumination image
Summary
In order to solve the problem of poor visual communication effect of impressionist painting colors and low accuracy of painting color enhancement by existing methods, this thesis proposes a research on the performance of impressionist painting color visual communication based on machine vision under the background of wireless network. is method can improve the vision, speed, and efficiency of communication, through the analysis of the characteristics of impressionist paintings, and determine the visual communication objects of impressionist painting colors. e process of visual communication is analyzed, and the color matching of impressionist painting is completed with the help of BP neural network algorithm. Based on the problems in the above methods, this paper proposes a new performance research method of impressionist painting color visual communication based on machine vision.
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