High-resolution sar image classification method based on co-sparse model

A classification method and sparse model technology, applied in character and pattern recognition, instruments, calculations, etc., can solve problems such as insufficient utilization of learned analytic operators, limited accuracy of image classification, etc., achieve fast speed, improve classification efficiency, high efficiency effect
CN107220659BActive Publication Date: 2019-10-25XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2019-10-25

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Abstract

The invention discloses a high-resolution SAR image classification method based on a co-sparse model. The invention solves the technical problem that the SAR image classification is limited to expressing images with a comprehensive sparse model, resulting in high classification time complexity. The process is as follows: select the initial pixel value matrix X in the SAR image to be classified; select the analytic operator to learn the initial sample; combine the projection subgradient method and the unified row norm tight frame method to learn the analytic operator Ω; use the augmented Lager The Langer method is used to solve the co-sparse coefficient Z; the co-sparse coefficient vector of each pixel corresponding to the pixel block is combined with the pixel value vector of the pixel block to obtain the feature vector; based on the SVM classifier classification, the feature vector of each pixel in the whole image is obtained The predicted label; display the predicted label result with a grayscale image. The invention can quickly obtain the sparse representation of the image, ensures the timeliness and classification accuracy of the SAR image classification, and is used for the classification of the high-resolution SAR image.
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Description

technical field

[0001] The invention belongs to the technical field of image processing, specifically for the classification of high-resolution SAR images, specifically a high-resolution SAR image classification method based on a co-sparse model, which is applied to the field of SAR image classification. Background technique

[0002] With the gradual improvement of Synthetic Aperture Radar (SAR) imaging technology, more and more applications of SAR images in various fields have prompted further research and development of SAR image classification technology. Due to the coherent speckle noise in the original SAR image, the traditional image classification methods in the past are not applicable to SAR image classification. SAR image classification can be applied to resource detection, military reconnaissance, medical fields, crop growth monitoring, disaster hazard assessment, etc. The value and importance of SAR image applications, and SAR image classification methods need to ...

Claims

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