Multi-temporal remote sensing image change detection method based on FCM and evidence theory

Abstract

The invention discloses a multi-temporal remote sensing image change detection method based on FCM and the evidence theory, and the method is characterized in that the method comprises the steps: firstly solving the corresponding band difference of remote sensing images at two time phases, the amplitude values of variable vectors of the two time phases, and the cosine values of spectrum inclined angles of the two time phases; secondly taking the above values as the input of the FCM, and respectively obtaining a corresponding fuzzy division matrix, and enabling the fuzzy degree of each type of fuzzy division matrixes to serve as a quality function of the evidence theory; finally carrying out the fusion of the above three division matrixes through employing the evidence theory, obtaining a new fuzzy division matrix, and obtaining the final change detection result according to the above. The beneficial effects of the invention are that the method is based on the FCM and the D-S evidence theory, achieves the fusion of the band difference, the amplitude values of variable vectors and the cosine values of spectrum inclined angles through employing the evidence theory, inputs the above values into the FCM model and obtains a detection result, eliminates the uncertainty in change detection through the detection result, and enables the result of change detection to be more reliable and robust.

Description

technical field [0001] The invention relates to a multi-temporal remote sensing image change detection method based on FCM and evidence theory, and belongs to the technical field of remote sensing image processing. Background technique [0002] With the continuous accumulation of multi-temporal remote sensing data and the successive establishment of spatial databases, how to extract and detect change information from these remote sensing data has become an important research topic in remote sensing science and geographic information science. According to remote sensing images of different time phases in the same area, dynamic information such as cities and environments can be extracted to provide scientific decision-making basis for resource management and planning, environmental protection and other departments. [0003] Change detection of remote sensing images is to quantitatively analyze and determine the characteristics and process of surface changes from remote sensing...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above problems, many scholars try to solve them by adding different spatial neighborhood constraints to the FCM objective function, but the expression of spatial information and the selection of related parameters (such as the penalty parameter to control spatial information) are mostly based on priori Knowledge is determined, resulting in certain limitations in these algorithms

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