The Earth Environment Change Detection Method Based on the Variable Weight Markov Random Field Combined with the Space Gravity Model

Abstract

Abstract For the traditional earth environment change detection algorithm based on remote sensing image, only the band information of the image is utilized, and it is difficult to obtain the defect of the complete change detection result. Based on the spectral information of the image, the change detection method based on Markov random field model introduces the spatial correlation of pixels, which improves the accuracy of change detection to some extent. However, due to the over-use of spatial correlation in the process of introducing pixel spatial information, these methods have the disadvantage of poor detection results due to the fixed weight parameters in the modelling process. Aiming at the limitations of these methods, this paper proposes the environment of earth change detection method based on the variable weight markov random field combined with the space gravity model. Using the space gravitation model, the use of pixel spatial information is more reasonable, and the idea of variable weight is introduced to improve the defect that the change detection result is too smooth due to the fixed weight parameter. Experiments on real high-resolution remote sensing image datasets verify the effectiveness and feasibility of the proposed method.