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Change detection method for high-resolution remote sensing images based on multi-scale segmentation and fusion

A multi-scale segmentation, remote sensing image technology, applied in the field of hyperspectral remote sensing images, can solve the problems of inability to guarantee the integrity of detection results, low detection accuracy of high-resolution remote sensing images, etc., to improve accuracy, ensure integrity, and improve detection accuracy. Effect

Active Publication Date: 2020-06-09
HARBIN INST OF TECH
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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that the existing remote sensing image change detection technology has low detection accuracy for high-resolution remote sensing images and cannot guarantee the integrity of the detection results, and provides a high-resolution remote sensing image based on multi-scale segmentation and fusion Change detection method

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  • Change detection method for high-resolution remote sensing images based on multi-scale segmentation and fusion
  • Change detection method for high-resolution remote sensing images based on multi-scale segmentation and fusion
  • Change detection method for high-resolution remote sensing images based on multi-scale segmentation and fusion

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specific Embodiment approach 1

[0012] Specific implementation manner 1: The method for detecting changes in high-resolution remote sensing images based on multi-scale segmentation and fusion described in this embodiment, the specific process of the detection method is:

[0013] Step 1. Use a multi-scale segmentation algorithm to segment the multi-temporal high-resolution remote sensing image at a spatial scale. The spatial scale is divided into two parts: coarse scale and fine scale, and appropriate shape factors are selected to use top-down regional heterogeneity Gender guidelines to merge;

[0014] Step 2. Perform feature extraction on the object angle of the target in each scale image segmented in Step 1, use the object feature to describe the object itself, and then perform vector analysis with respect to remote sensing images of other time phases to obtain object difference maps of multiple scales ;

[0015] Step 3. Perform change information extraction and fusion on the object difference map of multiple sca...

specific Embodiment approach 2

[0021] Specific implementation manner 2: This implementation manner further illustrates the implementation manner 1. The specific method of using a multi-scale segmentation algorithm to perform spatial scale segmentation on multi-temporal high-resolution remote sensing images is:

[0022] Multi-scale segmentation uses a top-down region merging algorithm based on minimal heterogeneity to obtain image segmentation sequences of different scales of the input image, and combines shape heterogeneity to obtain merged regions. The heterogeneity is expressed as:

[0023]

[0024] Where h total Represents overall heterogeneity, Indicates the weight of spectral heterogeneity, satisfying h c And h s Represents spectral heterogeneity and shape heterogeneity respectively, and satisfies:

[0025]

[0026]

[0027] among them, Indicates the weight of each band, the number of bands is c, σ c Indicates the standard deviation of each spectral band; Represents the smoothness weight, h sm And h co ...

specific Embodiment approach 3

[0038] Specific embodiment 3: This embodiment further explains the first or second embodiment. The multi-scale is divided into coarse scale and fine scale, the scale parameter of the fine scale is 10-50, and the scale parameter of the coarse scale is 50-100.

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Abstract

A high-resolution remote sensing image change detection method based on multi-scale segmentation and fusion belongs to the technical field of hyperspectral remote sensing images. The present invention aims to solve the problem that the existing remote sensing image change detection technology has low detection accuracy for high-resolution remote sensing images and cannot guarantee detection results. question of completeness. The specific process of the present invention is as follows: using a multi-scale segmentation algorithm to perform spatial scale segmentation on multi-temporal high-resolution remote sensing images; performing feature extraction on objects in each scale image after segmentation, and using object features to describe the object itself , and then perform vector analysis on remote sensing images of other time phases to obtain object difference maps at multiple scales; extract and fuse change information on the obtained object difference maps at multiple scales to obtain the final total change result map. The invention is used for high-resolution remote sensing image change detection.

Description

Technical field [0001] The invention relates to a high-resolution remote sensing image change detection method, belonging to the technical field of hyperspectral remote sensing images. Background technique [0002] With the improvement of satellite resolution, the detailed information of high-resolution remote sensing satellite data is rich, and the amount of data has increased sharply. The increase in image data volume and complexity has made it more difficult to automatically identify changing areas in multi-temporal remote sensing images. The corresponding data processing technology has also increased. It is difficult to meet the accuracy requirements; and high-resolution remote sensing images have rich detailed information, obvious edges of various objects, and greatly increased noise. At this stage, most change detection methods based on feature domains and pixel levels cannot overcome the problem of insufficient detection accuracy. Target-level detection methods cannot over...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/13G06V10/462G06F18/253
Inventor 张钧萍郭庆乐李彤
Owner HARBIN INST OF TECH
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