Synthetic aperture radar (SAR) image bionic recognition method based on sample generation and nuclear local feature fusion

A sample image and recognition method technology, applied in character and pattern recognition, computer components, instruments, etc., can solve problems such as unstable feature extraction

Inactive Publication Date: 2013-04-03
BEIHANG UNIV
View PDF4 Cites 38 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The method of the invention can effectively remove the coherent noise interference in the SAR image, and overcome the problem of unstable feature extr

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Synthetic aperture radar (SAR) image bionic recognition method based on sample generation and nuclear local feature fusion
  • Synthetic aperture radar (SAR) image bionic recognition method based on sample generation and nuclear local feature fusion
  • Synthetic aperture radar (SAR) image bionic recognition method based on sample generation and nuclear local feature fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0047] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

[0048] The SAR image recognition method provided by the present invention first uses the K-SVD dictionary learning method for image denoising, and then uses the target centroid method to realize target area extraction; then combines local pattern quantization (Local Pattern Quantization, LPQ) and Gabor filtering method Extract and perform feature fusion, and finally use the bionic pattern recognition method to cover the high-dimensional geometric manifold for classification. Such as figure 1 As shown, it is the SAR image recognition method provided by the present invention, and each step will be described in detail below.

[0049] Step 1: Construct an over-complete training sample set.

[0050] Three types of military target optical images and SAR images adopted in the embodiment of the present invention are as follows: figure 2 as shown, figure...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a synthetic aperture radar (SAR) image bionic recognition method based on sample generation and nuclear local feature fusion and belongs to the field of image processing technologies and SAR target recognition. According to the method, a super complete training sample set is firstly constructed for training to obtain geometry manifold, then a sample to be recognized is recognized, specifically, each sample is firstly subjected to image denoising by a K-SVD dictionary learning method, and object region extraction is achieved by means of an object centroid method; and feature extraction is performed respectively by combining local phase quantization (LPQ) and a Gabor filtering method, feature fusion is performed, finally, classification is performed by covering of high-dimensional geometry manifold, and recognition is performed by a bionic mode. According to the SAR image bionic recognition method based on sample generation and nuclear local feature fusion, inhibiting effects of image coherent noises are obvious, SAR image features can be effectively extracted, the problem of the unstable extracted features, which is caused by changes of attitude angles of SAR images, is solved, the recognition accuracy is high, and the method has good robustness.

Description

technical field [0001] The invention belongs to the field of image processing technology and SAR target recognition, in particular to a SAR image bionic recognition method based on sample generation and nuclear local feature fusion, which can be applied to military and civilian target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) has good application prospects in the fields of modern battlefield perception and ground military strikes because it can obtain ground battlefield data all-weather and all-weather, making automatic target recognition based on SAR images ( Automatic Target Recognition, referred to as ATR) has been paid more and more attention by researchers, and has gradually become one of the research hotspots at home and abroad. In the research of SAR target recognition, many research institutions at home and abroad are mostly based on the Moving and Stationary Target Acquisition and Recognition (MSTAR) database provided by the US DARPA / ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/66
Inventor 李景文翟懿奎朱燕青
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap