Segmentation method for synthetic aperture radar images in consideration of multi-scale Markov field

A synthetic aperture radar, multi-scale segmentation technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problems of easy loss of edge detail information in segmentation results, large amount of MAP estimation calculation, insufficient speckle suppression, etc. Small error rate, small impact, small speckle noise effect

Inactive Publication Date: 2009-11-25
WUHAN UNIV
View PDF0 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The method based on the MRF field has high segmentation accuracy for images with few categories, and makes full use of statistical and texture characteristics, but the MAP estimation is computationally intensive and time-consuming.
Based on the multi-scale MRF field method, a new multi-scale random field model is u

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
  • Segmentation method for synthetic aperture radar images in consideration of multi-scale Markov field
  • Segmentation method for synthetic aperture radar images in consideration of multi-scale Markov field
  • Segmentation method for synthetic aperture radar images in consideration of multi-scale Markov field

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The flow of the SAR image segmentation method of the present invention considering the multi-feature multi-scale MRF field is as follows figure 1 shown, including the following steps:

[0018] (1) Use the gray level co-occurrence matrix to perform texture analysis on the original image Y to obtain the texture feature image Y'. Assuming that there are N gray values ​​in a certain area of ​​the image, the gray co-occurrence matrix corresponding to this area is a matrix of N×N order, and the value of the element (i, j) in the gray co-occurrence matrix indicates that along a certain direction, the The relative frequency with which two adjacent pixels with gray levels i and j separated by a distance d appear on the image. Such a matrix is ​​symmetric and has a function of the angular relationship between two adjacent pixels. The co-occurrence matrix can be calculated on the whole image, and the co-occurrence matrix can also be calculated in the small window of the scanned ...

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 segmentation method for SAR images in consideration of multi-feature multi-scale MRF field, which is used for the treatment of remote sensing images, the method comprises the steps of: (1) extracting texture information from original images by utilizing a gray level co-occurrence matrix, and performing multi-scale segmentation on the resultant texture characteristic images; (2) detecting edge information of the original images by means of wavelet transformation in order to obtain edge characteristic images; (3) incorporating texture multi-scale segmentation result with edge characteristics by a linear weighting method, namely, corresponding pixel points of the two images are directly subjected to weighted stack to obtain final segmentation result. The invention reduces erroneous segmentation rate of SAR images and outstandingly remains detailed information of the images like edge information while eliminating speckle noise.

Description

technical field [0001] The invention relates to a synthetic aperture radar image segmentation method, in particular to a SAR image segmentation method considering multi-features and multi-scale Markov fields, and belongs to the field of remote sensing image processing. Background technique [0002] Synthetic Aperture Radar (SAR) has the characteristics of all-weather, large area, high resolution, and ability to penetrate the surface clouds and fog, so that it can obtain a large amount of information in a short time, which also makes the application of SAR images become a research field in the field of remote sensing. hotspots. With the development of spaceborne SAR systems at home and abroad, a large amount of spaceborne SAR image data has been obtained. Compared with the rapid growth trend of SAR data sources, the research on SAR image processing and analysis technology, which is the basis of SAR data application, is relatively lagging behind. SAR image segmentation is an ...

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): G06T5/00G06T7/60
CPCG06V10/54
Inventor 徐川眭海刚刘俊怡马国锐
Owner WUHAN 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