Rapid multi-scale super-pixel segmentation method for synthetic aperture radar image

A technology of synthetic aperture radar and superpixel segmentation, which is applied in the field of remote sensing image interpretation, can solve the problems of low efficiency of SAR images, achieve good image local detail retention ability, improve execution efficiency, and maintain the effect of image boundaries

Pending Publication Date: 2020-12-22
HANGZHOU SHIPING INFORMATION & TECH
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AI Technical Summary

Benefits of technology

This technology improves upon previous methods such as comparing pixels between two or more images. By defining an algorithm called Minimal Spatial Trees (MSGs), it create a unique way to represent complex objects like 3D shapes without overlapping them together. These MSV's help us analyze large amounts of data quickly while still capturing important detail about each object being observed at once. Overall, these techniques improve the accuracy and speed of generating high quality digital maps from synthetic aperture radar imagery (SAR).

Problems solved by technology

This patented technical problem addressed in this patents relates to improving efficient creation of sophisticated radars capable of accurately detecting objects without being affected by interference caused by other things like rain gear during operation.

Method used

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  • Rapid multi-scale super-pixel segmentation method for synthetic aperture radar image
  • Rapid multi-scale super-pixel segmentation method for synthetic aperture radar image
  • Rapid multi-scale super-pixel segmentation method for synthetic aperture radar image

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Embodiment Construction

[0041] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0042] A fast multi-scale superpixel segmentation method for synthetic aperture radar images, the specific steps are as follows:

[0043] A. For SAR images, define pixel gray similarity, edge intensity similarity and image inhomogeneity similarity;

[0044] B. Represent the SAR image in a graph structure;

[0045] C. Using the Kruskal algorithm to realize the minimum spanning tree of SAR images;

[0046] D. Realize fast multi-scale superpixel segmentation of SAR image based on minimum spanning tree;

[0047] E. Obtain superpixel segmentation boundaries based on the segmentation results and generate SAR image segmentation results.

[0048] The specific operation method of step A is:

[0049]First, a pixel similarity measure needs to be defined for SAR images. Due to the presence of coherent speckle noise, traditional pixel-based gray-level similarity measures

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Abstract

The invention discloses a rapid multi-scale super-pixel segmentation method for a synthetic aperture radar image. The method comprises the following steps: measuring the final similarity of two pixelsin combination with backscattering gray similarity, edge information similarity and homogeneity similarity; performing graph structure representation on the SAR image; constructing a minimum spanningtree for the SAR image; sAR image fast multi-scale super-pixel segmentation is achieved based on the minimum spanning tree, a super-pixel segmentation boundary is obtained based on a segmentation result, and an SAR image segmentation result is generated. According to the invention, any number of superpixels with a tree structure can be generated immediately, so that superpixel results of different levels can be segmented. According to the multi-scale super-pixel segmentation method, image boundaries can be well kept, the good image local detail keeping capacity is achieved, the segmentation result of any scale can be generated for the SAR image in real time, target information of different sizes can be easily obtained, and the execution efficiency is remarkably improved.

Description

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Claims

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Application Information

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Owner HANGZHOU SHIPING INFORMATION & TECH
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