Method of detecting flood disaster changes through object-level high-resolution SAR (synthetic aperture radar) images

A high-resolution, change detection technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of high cost and high complexity of sample acquisition

Inactive Publication Date: 2015-02-18
HOHAI UNIV
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For example, Cheng Mingyue et al. trained the texture of the sample image through the fuzzy weighted support vector machine to obta

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  • Method of detecting flood disaster changes through object-level high-resolution SAR (synthetic aperture radar) images
  • Method of detecting flood disaster changes through object-level high-resolution SAR (synthetic aperture radar) images
  • Method of detecting flood disaster changes through object-level high-resolution SAR (synthetic aperture radar) images

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Embodiment Construction

[0066] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0067] Such as figure 1 As shown, the method proposed by the present invention mainly consists of geometric registration, noise suppression based on contourlet transform and marker point extraction, watershed segmentation and region merging based on marker points, false target elimination and change detection.

[0068] The image registration adopts the ENVI software of ITT Vision Solutions (Visual Information Solutions) in the United States, so I won’t repeat them here;

[0069]The contour wave a...

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Abstract

The invention discloses a method of detecting flood disaster changes through object-level high-resolution SAR (synthetic aperture radar) images and aims to solve the problem that a false target possibly existing in an SAR image and similar to a water region in geometrical characteristics and spectral characteristics causes great 'pseudo-changes' and causes difficulty and disturbances to flood disaster change detection. Each time-phase image is subjected to contourlet transform; image noise is suppressed at the premise of keeping image edge characteristics, an optimal decomposition scale is selected through simple sample training, and the position of a mark point in a possible area of a water body is quickly acquired through block histogram statistics, on the optimal decomposition scale. Contour information of the water body is acquired through a mark-point-based watershed segmentation and region merging strategy, and interference of the false target is further eliminated through discrimination rules based on multiple features. Finally, water contours extracted from multiple time-phase images are directly compared according to registration results, and a region having water body changes is obtained.

Description

technical field [0001] The invention relates to an object-level high-resolution SAR image flood disaster change detection method, which belongs to the technical field of high-resolution SAR image flood disaster change detection. Background technique [0002] Flood disasters refer to phenomena such as mountain torrents, dam breaks, submerged farmland, and house damage caused by precipitation. They are currently one of the most serious natural disasters in the world. Due to the advantages of strong timeliness and wide coverage, remote sensing images have become an important means of flood disaster monitoring and assessment. Since the absorption rate of electromagnetic waves in the range of 0.14-215Lm by water bodies is significantly higher than that of other ground objects, water bodies usually appear as areas with continuous distribution and low overall brightness. This is also the basis for detecting changes in flood disasters using remote sensing images. . [0003] At pre...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T2207/10044G06T2207/20152
Inventor 王超石爱业高红民徐立中黄凤辰
Owner HOHAI UNIV
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