Watershed algorithm-based high spatial resolution multi-spectral remote sensing image segmentation method

A technology of high spatial resolution and watershed algorithm, applied in image enhancement, image data processing, computing, etc., can solve problems such as slowing down the speed of merging, over-segmentation, and little improvement in merging results

Inactive Publication Date: 2010-12-22
BEIJING NORMAL UNIVERSITY
View PDF0 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Watershed segmentation will cause serious over-segmentation. When some scholars perform over-segmentation and merging, they consider multiple information such as texture, mean, and variance to improve the effect of m...

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
  • Watershed algorithm-based high spatial resolution multi-spectral remote sensing image segmentation method
  • Watershed algorithm-based high spatial resolution multi-spectral remote sensing image segmentation method
  • Watershed algorithm-based high spatial resolution multi-spectral remote sensing image segmentation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0023] The purpose of the present invention is to solve the problem of segmentation of high spatial resolution optical remote sensing images. The specific steps are as follows: firstly, the gradient image is obtained from the multi-spectral image, and then the gradient image is segmented by the watershed algorithm, and finally the regions are merged according to the merge algorithm using the similarity between the regions to obtain the final segmentation result.

[0024] Because the watershed algorithm is sensitive to gradients and mainly uses gradient information for segmentation, the present invention first uses the gradient algorithm of the multispectral image to find the gradient.

[0025] Among them, the gradient algorithm of multi-spectral image comprehensively considers each band, so that all significant details can be reflected on the gradient matrix, and the watershed algorithm uses more information. The problem that the watershed algorithm cannot process multi-spectral re...

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 relates to a watershed algorithm-based high spatial resolution multi-spectral remote sensing image segmentation method, and aims to solve the segmentation problem of a high spatial resolution multi-spectral remote sensing image. The method comprises the following steps of: solving the gradient of the multi-spectral image by using a multi-spectral gradient algorithm to obtain a gradient image, then segmenting the gradient image by using a watershed algorithm, and finally performing region merging according to a merging algorithm by using the similarity between regions to obtain a final segmentation result.

Description

Technical field: [0001] The invention belongs to the technical field of remote sensing image processing and image segmentation, and is an image segmentation method based on a watershed algorithm that can process multi-spectral remote sensing images and can eliminate the over-segmentation phenomenon of the watershed algorithm. Background technique: [0002] The current remote sensing data presents the characteristics of high space, high spectrum and high time resolution. Its types and capacity have reached unprecedented scale. Visual interpretation of massive data has long been recognized as an impossible task, and it must rely on computers to automatically interpret information. . High-resolution images refer to images with a spatial resolution of more than 5 meters. The highly detailed image information and complex texture changes make the phenomenon of different spectra of same objects and same spectra of foreign objects more prominent, which brings great difficulties to the ex...

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): G06T5/00G01S17/89
Inventor 余先川康增基
Owner BEIJING NORMAL 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
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