A Polarization SAR Image Classification Method Based on Multi-Feature Fusion

Abstract

The invention discloses a polarization SAR image classification method based on multi-feature fusion. The present invention firstly extracts the polarization feature vector of the polarimetric SAR image to be classified to obtain a high-dimensional polarization feature set; extracts the morphological section feature vector of the image SPAN processing result to obtain a high-dimensional morphological feature set; After the features are subjected to the dimensionality reduction processing of the locality-preserving discrimination analysis, the image pixels with known category labels are selected to form the training sample set, and then the remaining pixels of the entire image are selected as the classification sample set; the two types of low-dimensional features are respectively passed through the The SVM of the maximum posterior probability obtains the category label and the corresponding posterior probability of the pixel points in each case; the summation criterion or the adaptive weighted summation criterion is used to combine the posterior probability vectors of each pixel in the two situations According to the principle of maximum a posteriori probability, the final classification result of high-resolution polarimetric SAR images is obtained. The implementation of the invention helps to improve the classification accuracy and efficiency of resolving polarimetric SAR images.

Description

technical field

[0001] The invention belongs to radar image processing and interpretation technology, that is, ground object classification processing is performed on high-resolution polarization synthetic aperture radar images, and in particular relates to a polarization SAR image classification method based on multi-feature fusion. Background technique

[0002] In recent years, my country has successfully applied Synthetic Aperture Radar (SAR) in various fields. The successful application of SAR depends on effective SAR image processing and interpretation technology, and its premise is the classification technology of SAR image. Through classification, the ground object information in SAR images can be effectively obtained, and it can provide assistance for various applications such as urban planning, crop and forest observation, disaster assessment, and ground target recognition. Therefore, SAR image classification technology occupies a very important position.

[0003] ...

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