Application of Markov random field model in the design of digital pattern painting

The principle of camouflage pattern painting is to derive the characteristics of surrounding background, such as color and texture, and make the characteristics reappear in the target camouflage. Color and texture are the key elements in the design of pattern painting. We derive major colors of surrounding background using the clustering method, and make the texture parameters reappear in the design of digital pattern painting using the Markov random field method. Then, the digital pattern painting design system is constructed. To validate the effectiveness of the system, the experiment is organized. A piece of satellite optical picture is used as the background, and in the picture, one small district is selected as the target. The digital pattern painting is designed by the constructed system. The experimental results show that the designed pattern painting can blend with the surrounding background, which has good camouflage effectiveness. The pattern painting design system can be referenced in the design of distortion pattern painting.