Change detection method for remote sensing images based on an improved Markov random field

摘要

The fixed weights between the center pixel and neighboring pixels are used in the traditional Markov random field for change detection, which will easily cause the overuse of spatial neighborhood information. Besides the traditional label field cannot accurately identify the spatial relations between neighborhood pixels. To solve these problems, this study proposes a change detection method based on an improved MRF. Linear weights are designed for dividing unchanged, uncertain and changed pixels of the difference image, and spatial attraction model is introduced to refine the spatial neighborhood relations, which aims to enhance the accuracy of spatial information in MRF. The experimental results indicate that the proposed method can effectively enhance the accuracy of change detection.