High-performance implementation method for multi-scale segmentation of remote sensing images

A multi-scale segmentation, remote sensing image technology, applied in image enhancement, image data processing, electromagnetic wave re-radiation and other directions, can solve the problems of not establishing multi-scale topological relationships and not many solutions.

A multi-scale segmentation, remote sensing image technology, applied in image enhancement, image data processing, electromagnetic wave re-radiation and other directions, can solve the problems of not establishing multi-scale topological relationships and not many solutions.

CN101706950BInactive Publication Date: 2012-04-25REMOTE SENSING APPLIED INST CHINESE ACAD OF SCI
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  • High-performance implementation method for multi-scale segmentation of remote sensing images
  • High-performance implementation method for multi-scale segmentation of remote sensing images
  • High-performance implementation method for multi-scale segmentation of remote sensing images

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Embodiment Construction

[0034] figure 1 It is a schematic diagram of the multi-scale segmentation method of high-performance remote sensing images, in which the main part of the image segmentation is realized by the high-performance computing method of parallel segmentation, and the multi-scale segmentation part is realized by the circular scale merging method, which can efficiently realize the multi-scale segmentation of the image. The specific implementation technical process of the high-performance implementation method for multi-scale segmentation of multi-scale remote sensing images described in the present invention is as follows: figure 2 as shown, figure 2 Contains 12 processing units. Wherein, the working process of the high-performance multi-scale segmentation of the image is (this embodiment takes the mean shift segmentation algorithm as an example):

[0035] After the image data is pre-processed (such as denoising, enhancement, etc.), according to the principle of the mean shift segme...

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Abstract

The invention provides a high-performance implementation method for multi-scale segmentation of remote sensing images, and in particular a method for implementing fast and multi-scale image segmentation of large amount of remote sensing images and establishing the structural relationship of segmentation results in the process of high-resolution remote sensing image information extraction. The method comprises the following steps: on the basis of analyzing the implementation procedure of the algorithm and finding out the computing-intensive segment of the algorithm, realizing the parallel segmentation of the algorithm-intensive segment based on MPI and OMP models, and carrying out date join on the parallel segmentation results; implementing the multi-scale image segmentation by storing theinitial segmentation results of the algorithm and merging the subsequent multi-scale remote sensing images; and establishing a multi-scale object topological relation model. The generated multi-scalesegmentation region and corresponding hierarchical relationship can be applied to various services; and the corresponding implementation method is applicable to various segmentation algorithms such as mean shift and the like, and can greatly improve the data amount processed by algorithm and the processing efficiency.

Description

technical field [0001] The present invention relates to remote sensing image processing technology and remote sensing image information extraction method, in particular, to multi-scale segmentation of remote sensing images and its high-performance implementation method, and the establishment of scale topological relationship of segmentation results. The present invention is applicable to various remote sensing images High performance implementation of the split method. Background technique [0002] The object-oriented remote sensing image analysis method has been widely used in current remote sensing image processing, information extraction and analysis, target recognition, classification and other applications, and has become an important method for remote sensing image processing and analysis, especially high-resolution remote sensing image processing and analysis. Among them, object extraction, feature calculation and feature analysis are important steps in the process of...

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Application Information

Patent Timeline
25 Apr 2012
Publication
CN101706950B
IPC
G06T5/00; G01S17/89
Inventors
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