Change Detection Method of Remote Sensing Image Based on Slow Feature 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: 2016-08-17
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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  • Change Detection Method of Remote Sensing Image Based on Slow Feature Analysis
  • Change Detection Method of Remote Sensing Image Based on Slow Feature Analysis
  • Change Detection Method of Remote Sensing Image Based on Slow Feature 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 change detection method based on slow feature analysis. The invention introduces the slow feature analysis method into the change detection of multi-temporal remote sensing images, and the slow feature analysis method fully considers the spatial correspondence between the multi-temporal remote sensing images. The original theory for continuous signal analysis was developed into a change detection algorithm based on discrete data sets. The slow feature analysis method can extract the invariant features in the multi-temporal remote sensing image data set as the feature space. In this feature space, the spectral differences between the multi-temporal remote sensing images are suppressed and the real changes are highlighted, thereby improving the change detection accuracy. . At the same time, the slow feature analysis method is simple to implement and fast in operation.

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 cover 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 objects in the same area at different times (Singh, A. (1989). "Review Article Digital change detection techniques using remotely-sensed data." International Journal of Remote...

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Application Information

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