Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Active contour synthetic aperture radar (SAR) image segmentation method based on Fisher distribution

An image segmentation and active contour technology, applied in the field of image processing, can solve the problems of slow segmentation, time-consuming re-initialization steps, insufficient development of coherent spots in SAR images, etc.

Inactive Publication Date: 2012-07-04
ZHEJIANG GONGSHANG UNIVERSITY
View PDF3 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the Gamma distribution can better describe the uniform area SAR image data in the case of medium and low resolution, as the resolution increases, the coherent spots of the SAR image are not fully developed, and the uniformity decreases, and the Gamma distribution generally cannot describe it well. Therefore, the current method based on Gamma distribution cannot be used for segmentation processing of high-resolution SAR images.
Second, the existing level set SAR image segmentation methods generally use the signed distance function to represent the level set function, which often requires time-consuming reinitialization steps during the curve evolution process, making the segmentation speed slow

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
  • Active contour synthetic aperture radar (SAR) image segmentation method based on Fisher distribution
  • Active contour synthetic aperture radar (SAR) image segmentation method based on Fisher distribution
  • Active contour synthetic aperture radar (SAR) image segmentation method based on Fisher distribution

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0045] Embodiment: a kind of active contour SAR image segmentation method based on Fisher distribution, comprises the following steps:

[0046] In the first step, the Fisher distribution is used to describe the statistical characteristics of the SAR image, and the energy functional function based on the Fisher distribution is established according to the regional competition model.

[0047] In order to better describe the SAR image under high-resolution conditions, the Fisher distribution is used to describe the statistical characteristics of the SAR image, assuming that the SAR image to be segmented It consists of two parts, which are the target area (foreground) and background area (background), assuming that the two regions obey the independent Fisher probability and statistics model, the following energy functional of SAR image segmentation can be established by the regional competition model, as Equation 1:

[0048] ,

[0049] in, is a closed curve with zero l...

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 an active contour synthetic aperture radar (SAR) image segmentation method based on Fisher distribution, which mainly aims to overcome the disadvantage of existing Gamma distribution to the SAR image segmentation technology, the method comprises the following specific implementation steps of (1) making use of Fisher distribution to fit the intensity statistical characteristics of an image area, and establishing an energy functional function based on the Fisher distribution according to a regional competition model; (2) introducing a level set function, and combining a length constraint item and a level set rule item to re-express the energy functional function obtained in step 1; (3) minimizing the energy functional function obtained in step 2 by adopting Euler-Lagrange calculus of variations, estimating Fisher distributed parameters by making use of logarithmic moment estimation, and then performing numerical solution to a partial differential equation, thereby obtaining the segmentation result of an SAR image. According to the method provided by the invention, the level set method evolutionary split curve and Fisher distributed parameter estimation are combined to minimize the energy functional function, thereby realizing segmenting SAR images.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to radar remote sensing application technology, and more specifically relates to a level set segmentation method of a synthetic aperture radar (Synthetic Aperture Radar, SAR) image. technical background [0002] Synthetic Aperture Radar (SAR) is an active sensor that uses microwaves for perception. Unlike optical sensors that rely on light sources, the SAR system is completely active acquisition, not subject to weather, light and other conditions, which makes SAR images better day and night and seasonal stability, and its all-weather, all-day visual ability , these advantages have become an indispensable earth observation technology in military, agricultural, urban planning and other application fields. With the continuous development of SAR equipment and imaging technology, the intelligent interpretation technology of SAR images is facing new challenges. As a key step in SAR image in...

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): G06T7/00
Inventor 王勋孔丁科范英豪章志勇
Owner ZHEJIANG GONGSHANG UNIVERSITY
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
Eureka Blog
Learn More
PatSnap group products