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Remote-sensing image variation detecting method based on slow characteristic analysis

A technology for remote sensing image and change detection, which is applied in the field of remote sensing image processing and can solve problems such as single situation

Active Publication Date: 2014-03-12
WUHAN UNIV
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Problems solved by technology

For multi-temporal remote sensing images, there are many types of changes in the changed pixels, so the differences of the changed pixels are various, while the differences of the unchanged pixels only include the spectral difference caused by the change of external conditions, and the situation is relatively simple

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  • Remote-sensing image variation detecting method based on slow characteristic analysis
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  • Remote-sensing image variation detecting method based on slow characteristic analysis

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specific Embodiment approach

[0101] Multiply the ordered eigenvector matrix by the standardized multi-temporal remote sensing images X and Y respectively, and subtract the corresponding elements of the multi-temporal remote sensing images X and Y to obtain the characteristic difference matrix SFA of the multi-temporal remote sensing images X and Y, namely , the feature difference image. The characteristic difference matrix SFA is composed of the characteristic difference SFA of each band j Formed matrix vector, characteristic difference SFA j is calculated as follows:

[0102] SFA j = w j x ^ - w j y ^ - - - ( 7 )

[0103] In formula (7), SFA j Indicates the characteristic difference of the jth band; w j is the jth eigenvector;...

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Abstract

The invention discloses a remote-sensing image variation detecting method based on slow characteristic analysis. A slow characteristic analysis approach is introduced in the detection of multi-temporal remote-sensing image variations; in the slow characteristic analysis approach, the space corresponding relation between the multi-temporal remote-sensing images is completely taken into account, and the original theory aiming at continuous signal analysis is developed into a variation detecting algorithm based on a discrete data set. By utilizing the slow characteristic analysis approach, invariant characteristics can be extracted from a multi-temporal remote-sensing image data set to serve as a characteristic space; in the characteristic space, the spectrum difference between the multi-temporal remote-sensing images is restrained, and true variation is highlighted, so that the variation detection accuracy can be enhanced. The slow characteristic analysis approach is simple to perform and high in arithmetic speed.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, in particular to a remote sensing image change detection method based on slow feature analysis. Background technique [0002] Human activities have had a huge impact on the earth's surface environment, which is reflected in various aspects such as environmental changes and urban development. Therefore, obtaining real-time and accurate changes in the earth's surface coverage is of great significance for environmental monitoring and resource management (Lu, D., P. Mausel, E. Brondizio and E. Moran (2004). "Change detection techniques." International Journal of Remote Sensing 25(12):2365-2401.). [0003] Change detection refers to the determination of surface changes by observing the distribution of ground features in the same area at different times (Singh, A. (1989). "Review Article Digital change detection techniques using remotely-sensed data. "International Journal of R...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46
Inventor 武辰杜博张良培
Owner WUHAN UNIV
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