Polsar image feature classification method based on dfic superpixels

A ground object classification and superpixel technology, applied in the field of image processing, can solve the problems of poor superpixel segmentation effect, no decomposition features, poor classification effect, etc., to improve the classification accuracy, improve the clarity accuracy, and improve the segmentation effect. Effect

Active Publication Date: 2020-04-07
XIDIAN UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method has achieved good results due to the use of the polarization scattering similarity between pixels, the disadvantage of this method is that in PolSAR images with more speckle noise, Can not overcome the impact of speckle noise on object classification
The disadvantage of this method is that because the method uses pseudo-color images for superpixel segmentation, it fails to take advantage of the scattering characteristics of the image, so the superpixel segmentation effect in complex areas is poor, and the classification effect becomes poor. Difference
The disadvantage of this method is that when generating superpixels, this method does not use the decomposition features of PolSAR images, which makes the superpixel segmentation lines generated during superpixel segmentation inaccurate

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
  • Polsar image feature classification method based on dfic superpixels
  • Polsar image feature classification method based on dfic superpixels
  • Polsar image feature classification method based on dfic superpixels

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The present invention will be further described in detail below with reference to the accompanying drawings.

[0039] Refer to the attached figure 1 The implementation steps of the present invention are further described in detail.

[0040] Step 1. Input a PolSAR image to be classified.

[0041] Step 2. Perform Claude target decomposition.

[0042] The Claude target decomposition is performed on the PolSAR image of the polarimetric synthetic aperture radar, and seven features are obtained. The steps of the Claude target decomposition are as follows:

[0043] Refinement Lee filtering for polarimetric synthetic aperture radar PolSAR images.

[0044] Select a decomposition window of 7 × 7 pixels, decompose the refined Lee-filtered image, and select 7 features that contain all the information of the original PolSAR image from the decomposed feature map: entropy , Anisotropy, Reflection Angle: Alpha, Beta, Gamma, Delta, Lambda.

[0045] Step 3. Initialize superpixels. ...

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 PolSAR image ground object classification method based on DFIC superpixels. The implementation steps of the present invention are: (1) input polarization synthetic aperture radar PolSAR image; (2) carry out Claude target decomposition to PolSAR image; (3) initialize superpixel information; (4) calculate the feature between pixel points (5) update superpixels; (6) construct convolutional neural network; (7) classify PolSAR images; (8) iteratively cluster DFIC superpixels with decomposed features to optimize classification results. Compared with the superpixel segmentation method of the prior art, the present invention has the advantages of accurate segmentation boundary and compact interior of the superpixel, and has the advantages of high classification accuracy and no influence of noise points compared with the single pixel classification method of the prior art. The invention can be used for the classification of polarimetric synthetic aperture radar PolSAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a polarimetric synthetic aperture radar PolSAR (Polarimetric Synthetic Aperture Radar) image feature based on decomposition feature iterative clustering DFIC (Decomposition Feature Iterative Clustering) superpixels in the field of image classification technology Classification. The invention can be used to classify the ground objects in the image obtained by the polarization synthetic aperture radar PolSAR. Background technique [0002] Polarimetric Synthetic Aperture Radar PolSAR has become one of the research hotspots in the field of remote sensing due to its advantages of all-weather, all-time, and unaffected by weather. Therefore, more and more experts and scholars are devoted to the research of PolSAR images of polarimetric synthetic aperture radar. Among them, the classification of ground objects of PolSAR images of polarimetric synthetic aperture radar is ...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/13G06V10/462G06F18/24G06F18/214
Inventor 侯彪焦李成杨晨马晶晶马文萍王爽白静
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