Polarized SAT (synthetic aperture radar) image classification method based on improved affinity propagation clustering

A technology of neighbor propagation and classification method, which is applied in the field of image processing, can solve problems such as unbearable calculation and storage, arbitrary division of regions, and inability to effectively distinguish, and achieve the effect of reducing calculation and storage

Inactive Publication Date: 2013-07-03
XIDIAN UNIV
View PDF1 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are two defects in the H/α classification: one is that the division of regions is too arbitrary; the other is that when several different features coexist in the same region, they cannot be effecti

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
  • Polarized SAT (synthetic aperture radar) image classification method based on improved affinity propagation clustering
  • Polarized SAT (synthetic aperture radar) image classification method based on improved affinity propagation clustering
  • Polarized SAT (synthetic aperture radar) image classification method based on improved affinity propagation clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0033] Step 1, filter the polarimetric SAR image to be classified.

[0034] Select a polarimetric SAR image to be classified, and filter the polarimetric SAR image to be classified to remove speckle noise. The filtering methods that can be used include polarimetric whitening filtering, Boxcar filtering, refined polarimetric LEE filtering and unsupervised classification based Filtering method, etc., the filtering method adopted in the present invention is refined polarization LEE filtering method, and the size of the filtering window is 7×7.

[0035] Step 2, decompose the coherence matrix T of each pixel in the filtered polarimetric SAR image into four components, and obtain the volume scattering power P of each pixel v , dihedral scattered power P d , surface scattering power P s and the helical scattering power P h .

[0036] (2a) Read in each pixel of the filtered im...

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 polarized SAR (synthetic aperture radar) image classification method based on improved affinity propagation clustering. The problem of low classification accuracy in the existing unsupervised polarized SAR classification method is mainly solved. The method comprises the implementation steps of: carrying out four component decompositions on each pixel point, extracting four scattering powers of each pixel point; dividing an image according to the obtained scattering powers to obtain four classes; equally dividing each obtained class into 20 small classes; clustering the 20 small classes in each class by the improved affinity propagation clustering to obtain the pre-classification result of the image; and finally, carrying out iterative classification on a pre-classified image by a Wishart classifier to obtain the final classification result. Compared with the classical classification method, for the method disclosed by the invention, the division on a polarized SAR image is stricter; the classification effect is better; the computation complexity is small; and the polarized SAR image classification method can be used for carrying out terrain classification and target identification on the polarized SAR image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to the application in the field of classification of polarimetric SAR images, in particular to a method for classifying polarimetric SAR images based on the nearest neighbor propagation clustering algorithm, which can be used for the classification of polarimetric SAR images classification and object recognition. Background technique [0002] Polarization SAR radar can obtain richer target information, and has a wide range of research and application values ​​in agriculture, forestry, military, geology, hydrology and oceans, such as the identification of ground object types, crop growth monitoring, yield evaluation, Object classification, sea ice monitoring, land subsidence monitoring, target detection and marine pollution detection, etc. The purpose of polarimetric SAR image classification is to use the polarization measurement data obtained by airborne or spaceborne polari...

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): G06K9/62
Inventor 王爽焦李成刘亚超侯小谨侯彪刘坤张涛
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