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SAR image target recognition method

An automatic target recognition and image technology, applied in the field of image processing, can solve the problems affecting the SAR automatic target recognition rate, the feature dimension is too large, and the time consumption is long, so as to shorten the running time, reduce the feature dimension, and improve the recognition rate. Effect

Inactive Publication Date: 2013-12-04
XIDIAN UNIV
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Problems solved by technology

So far, the research on feature extraction at home and abroad has become increasingly mature and many feature extraction methods have emerged, such as based on K-L transform, Radon transform, and manifold learning, etc., but they still have too large feature dimensions, complex calculations, and long time consumption. The problem seriously affects the recognition rate of SAR automatic targets

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Embodiment Construction

[0022] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0023] Step 1. Input the SAR image and perform Haar wavelet transform on it to obtain a training sample matrix and a testing sample matrix.

[0024] (1a) Input N SAR target pictures when the depression angle is 17° in the MSTAR database as training samples, and input N′ SAR target pictures when the depression angle is 15° in the MSTAR database as test samples;

[0025] (1b) Haar wavelet transform is performed on the input N training sample images and N′ test sample images respectively, to obtain the wavelet low-frequency coefficients of all images, and splicing them in columns to obtain the SAR image training sample matrix X=(x 1 ,x 2 ,...,x N )∈R m×N And test sample matrix X′=(x 1 ',x 2 ',...,x N′ ') ∈ R m×N′ , where m represents the number of low-frequency coefficients of a SAR image, R represents a set of real numbers, in the example of the present invention, N=69...

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Abstract

The invention discloses an SAR image target recognition method which mainly solves the problems that in the prior art, feature dimensions of a sample are too large, computation is complex, and consumed time is long. The SAR image target recognition method is implemented in the following steps: (1) an SAR image is initialized to obtain a training sample matrix and a test sample matrix; (2) the Johnson-Lindenstrauss theory and limited equidistance RIP conditions are used for constructing a sparse measurement matrix; (3) according to the sparse measurement matrix, the training sample matrix and the test sample matrix are subjected to dimensionality reduction and normalization to obtain a normalized sample matrix; (4) according to the normalized sample matrix, a nearest neighbor classifier is used for obtaining a category label of the tested sample. Compared with the prior art, the SAR image target recognition method reduces the feature dimensions of the sample and computation complexity, increases SAR target recognition precision and arithmetic speed, and can be used for image processing.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to synthetic aperture radar (SAR) automatic target recognition. Background technique [0002] SAR automatic target recognition integrates the current pattern recognition theory and signal processing technology, and uses computers to automatically analyze, detect, locate, classify and identify targets on information. SAR image automatic target recognition, as an important part of SAR image interpretation and analysis, has important civil and military value, and has increasingly become a research hotspot in the field of image processing and pattern recognition at home and abroad. [0003] SAR image automatic target recognition mainly includes three steps, image preprocessing, feature extraction and target classification. Among them, feature extraction is the key issue of target recognition, which directly affects the effect of recognition. So far, the research on feature ex...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 于昕焦李成韩文婷马文萍马晶晶侯彪
Owner XIDIAN UNIV
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