Polarization SAR image classification method based on object orienting and spectral clustering

An object-oriented, classification method technology, applied in the field of image processing, can solve problems such as poor anti-noise ability, many misclassified points, and low classification accuracy, and achieve the goals of reduced time complexity, good regional consistency, and wide application range Effect

Active Publication Date: 2015-03-25
XIDIAN UNIV
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is simple and fast, but still has the disadvantages that the number of classification categories is fixed, and because only the scattering

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
  • Polarization SAR image classification method based on object orienting and spectral clustering
  • Polarization SAR image classification method based on object orienting and spectral clustering
  • Polarization SAR image classification method based on object orienting and spectral clustering

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0036] The technical content and effects of the present invention will be described in further detail below with reference to the accompanying drawings.

[0037] Reference figure 1 , The implementation steps of the present invention are as follows:

[0038] Step 1. Pre-processing the polarized synthetic aperture radar SAR data.

[0039] Read the coherence matrix T of the polarized synthetic aperture radar SAR data, and perform Lee filtering on the coherent matrix of the polarized synthetic aperture radar SAR data to obtain the coherence matrix of the filtered polarized synthetic aperture radar SAR data;

[0040] Extract the Pauli feature of the polarized synthetic aperture radar SAR data, and synthesize the color image of the polarized synthetic aperture radar SAR according to the Pauli feature. The coherence matrix of the polarized synthetic aperture radar SAR data is a 3*3*N matrix, and N represents polarization. The total number of pixels of synthetic aperture radar SAR, each pixe...

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 discloses a polarization SAR image classification method based on object orienting and spectral clustering. The method mainly solves the problem that the accuracy rate of image classification of a polarization synthetic aperture radar SAR in the prior art is low. The method comprises the implementation steps that (1), filtering is carried out on coherence matrixes of polarization SAR data, and the coherence matrixes are used for synthesizing a color image of the polarization synthetic aperture radar SAR; (2), related parameters of the polarization synthetic aperture radar SAR are set; (3), by means of combination with the related parameters of the polarization synthetic aperture radar SAR, all pixels of the color image of the polarization synthetic aperture radar SAR are combined to form super-pixel blocks; (4), all the super-pixel blocks of the color image of the polarization synthetic aperture radar SAR are combined; (5), class centers of the combined super-pixel blocks are calculated; (6), spectral clustering is carried out on the class centers of the super-pixel blocks to finish final classification. According to the method, the influence of noise is overcome, the accuracy rate of classification is increased, and the method can be applied to terrain classification and target recognition.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an object-oriented and spectral clustering-based polarization synthetic aperture radar SAR image classification method in the technical field of synthetic aperture radar, which can be used for forest fire monitoring, vegetation coverage, marine pollution etc. Background technique [0002] With the polarization synthetic aperture radar SAR more and more attention. There are endless methods for classifying polarimetric SAR data. According to whether manual guidance is required, it can be divided into supervised and unsupervised; according to the different algorithms used, it can be divided into statistics, knowledge, neural network, fuzzy statistics, wavelet, support vector machine and fractal, etc.; according to whether it needs Spatial information can be divided into area-based and pixel-based; according to the utilization of polarization information, it can be d...

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): G06K9/62G06T5/00
CPCG06F18/24137
Inventor 焦李成李玲玲李伟龙屈嵘杨淑媛侯彪王爽刘红英熊涛马文萍马晶晶
Owner XIDIAN 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