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SAR image multi-target fuzzy change detection method based on decomposition

A change detection and multi-target technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of speckle noise processing, weak image analysis ability of denoising, etc., to improve robustness, improve discrimination ability, and better detection effect of effect

Pending Publication Date: 2022-04-12
JIANGNAN UNIV
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Problems solved by technology

[0007] In order to enhance the analysis ability of SAR images and improve the detection accuracy of change detection tasks, the present invention provides a multi-target fuzzy change detection method based on decomposition. To deal with the problem of speckle noise, a new generation method of denoising differential image is proposed, that is, wavelet filtering + saliency detection method to obtain denoising differential image, which effectively removes spe

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  • SAR image multi-target fuzzy change detection method based on decomposition
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  • SAR image multi-target fuzzy change detection method based on decomposition

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Embodiment 1

[0060] This embodiment provides a method for detecting multi-target fuzzy changes in SAR images based on decomposition, see figure 1 , the method includes:

[0061] S1 obtains two SAR images of the same area in different periods through remote sensing satellites, and preprocesses the original images to obtain two SAR remote sensing satellite images with the same size.

[0062] S2 analyzes from the two conflicting perspectives of retaining details and removing noise, and constructs the corresponding target difference image. The logarithmic ratio operator is used to obtain the differential image that retains image information to the greatest extent, and wavelet filtering and a frequency domain-based saliency detection method are used to obtain the denoised differential image.

[0063] S3 constructs its objective function in an appropriate way according to different objective characteristics. We use FCM as the objective function for preserving details and FLICM as the objective...

Embodiment 2

[0095]This embodiment provides a decomposition-based two-target fuzzy change detection method. This example uses the detection results of the Yellow River dataset as an example for illustration, which includes two SAR images collected in June 2008 and June 2009, respectively. These are two SAR images that capture the changes in the area near the mouth of the Yellow River. This dataset records land surface changes due to cultivated land in the area near the mouth of the Yellow River.

[0096] In the embodiment, the experimental results are evaluated from two angles: one is the final binary change detection map, and the other is analysis using some quantitative means.

[0097] Five metrics were used to evaluate the effectiveness of the algorithm, including false positives (FP), false negatives (FN), total errors (OE), percent correct classification (PCC) and Kappa coefficient. Among them, assuming that the total number of pixels in the image is N, the number of false positives ...

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Abstract

The invention discloses an SAR image multi-target fuzzy change detection method based on decomposition, and belongs to the technical field of remote sensing monitoring. The method starts from two target points of detail reservation and noise removal, different difference images are generated for different targets, FCM and FLICM fuzzy clustering cost functions are respectively used to construct different target functions, a multi-target task is optimized through an MOEA/D mode, and finally, a new membership degree updating formula is adopted, and through a population iteration mode, a multi-target task is optimized. And calculating the final membership degree value of each pixel point with respect to different categories by using different weight distributions. Experiments prove that the method has a better detection effect on the SAR image. Meanwhile, more detailed analysis is carried out on two targets of detail reservation and noise removal, two target functions which conflict with each other are selected for the two targets so as to further improve the distinguishing ability, and the robustness of speckle noise is improved.

Description

technical field [0001] The invention relates to a decomposition-based multi-target fuzzy change detection method of a SAR image, which belongs to the technical field of remote sensing monitoring. Background technique [0002] Change detection is to determine the man-made or natural changes on the surface by analyzing remote sensing images of the same area obtained at different times. Change detection has been applied in many important fields, such as glacier ablation detection, disaster management, land cover detection and so on. [0003] With the continuous advancement of earth observation technology, we can now obtain different resolutions and different types of satellite remote sensing images more easily. Among them, Synthetic Aperture Radar (SAR) images are more The characteristics of strong penetrating ability have received extensive attention. However, due to its imaging principle, there is interference of scattered point noise in SAR images, so the analysis of SAR i...

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Application Information

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IPC IPC(8): G06T5/00G06T5/10G06V10/762G06V10/764
Inventor 方伟席超陆恒杨孙俊吴小俊
Owner JIANGNAN UNIV