Polarized SAR image target detection method based on deep stairway network

Abstract

The invention discloses a polarized SAR image target detection method based on a deep stairway network, comprising the following steps: inputting a polarized SAR image to be detected and performing Lee filtering on the polarized coherent matrix T; solving the filtered T to obtain a polarized covariance matrix C; performing Yamahachi decomposition on the polarized covariance matrix C to form a pixel-based characteristics matrix F; normalizing the F and extracting blocks for each element of the normalized characteristics matrix F1 and listing them in a column; forming a characteristics matrix F2 based on the image blocks; obtaining a training set D according to F2; using the SLIC algorithm in the super pixels to obtain a test set T; constructing a target detection model based on a deep stairway network; using the training data set D to train the target detection model; and utilizing the trained target detection model to classify the test data set T. According to the invention, a deep stairway network is adopted, which only uses a small amount of labeled samples to obtain high target detection precision. The present invention can be used for the classification of ground targets.

Description

【Technical field】 [0001] The invention belongs to the technical field of image processing, and in particular relates to a target detection method for polarimetric SAR images, which can be used for ground object classification, in particular to a polarimetric SAR image target detection method based on a depth ladder network. 【Background technique】 [0002] Synthetic Aperture Radar (SAR), as the only radar with all-weather and all-weather remote sensing imaging capabilities among various remote sensing methods, has an irreplaceable role in the field of remote sensing and has been widely used. The polarimetric synthetic aperture radar (polarimetric SAR) is a new SAR system radar based on the traditional SAR system, and its appearance has greatly expanded the application field of SAR. [0003] With the popularization of polarimetric SAR systems, the obtained full polarimetric data are becoming more and more abundant. How to quickly and accurately interpret images, and how to ef...

AI Technical Summary

Problems solved by technology

The above methods are all supervised classification methods, which require a large amount of class-labeled data, are costly, and require a lot of human and financial resources.

Images