A novel remote sensing image change detection algorithm based on Markov random field theory

Image change detection is based on the analysis in different time from the same area of two or more images, detect the feature in the region information changes over time. Remote sensing image change detection has been widely used in such as the dynamic monitoring of forest resources monitoring, the change of land cover and use, agricultural resources survey, urban planning layout, environmental monitoring and analysis, assessment of natural disasters, geographic data update and military reconnaissance in the strategic objectives (such as roads, Bridges, airports) of dynamic monitoring and many other fields. Markov generally is short for Markov property. It refers to a random variable sequence in relations, in turn, displaces, the distribution characteristics of N + 1 time, has nothing to do with the value of a random variable N moments ago. Due to the change detection task is aimed at a single time series scales images, applying Markov random field theory which can obtain better testing result.