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Visible light remote sensing image change detection method based on PCA-Kmeans

A remote sensing image and change detection technology, applied in the field of image processing, can solve the problems of difficulty in high-precision classification results, uncertainty of results, and low accuracy of change detection results, saving manpower, reducing noise and redundancy, and achieving superior performance. Effect

Inactive Publication Date: 2021-03-26
CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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Problems solved by technology

However, the key to this method is classification. The accuracy of change detection is equal to the accumulation of accuracy of classification results in different phases. Due to the segmentation problem of classification itself, it is often difficult to obtain high-precision classification results, which will lead to low accuracy of change detection results. and the uncertainty of the outcome

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  • Visible light remote sensing image change detection method based on PCA-Kmeans
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  • Visible light remote sensing image change detection method based on PCA-Kmeans

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Embodiment 1

[0053] A change detection method for visible light remote sensing images based on PCA-Kmeans.

[0054] combined with figure 1 , the steps of the present invention are as follows.

[0055] (1) Remote sensing images before and after input changes:

[0056] Input the two remote sensing images acquired in the same area with different time phases;

[0057] (2) Judging whether the input remote sensing image is a color remote sensing image, if step (3) is executed, otherwise, the input remote sensing image is executed step (4);

[0058] (3) Construct a single-channel grayscale remote sensing image:

[0059] (3a) Obtain a certain pixel of the color remote sensing image, select the color channel with the smallest brightness value from the three color channels of red R, green G, and blue B of the pixel, and use the brightness of the color channel as the The gray value of the pixel;

[0060] (3b) Step (3a) is repeated until all pixels in the color remote sensing image are processed,...

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Abstract

The invention discloses a visible light remote sensing image change detection method based on PCA-Kmeans. The method comprises the following steps: inputting two remote sensing images of different time phases in the same region, obtaining two time phase remote sensing image grey-scale maps, obtaining a remote sensing image difference map by using a subtraction method, performing dimension reduction on the difference map based on a PCA algorithm to obtain a feature space vector, and classifying feature vector spaces based on a K-Means algorithm to obtain a change detection result; performing contour detection on the change detection result based on an edge detection algorithm to obtain a bounding box, and finally filtering and merging the detected change area bounding box based on an NMS algorithm. Change detection images of different types of ground objects can be obtained respectively, and the invention has a wide application range and high detection precision and can be applied to the technical field of dynamic monitoring of different time phase remote sensing image change detection, ground object change detection before and after an earthquake, ground object change detection before and after a flood and the like.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for detecting changes in visible light remote sensing images based on PCA-Kmeans. The present invention can respectively obtain the change detection images of different types of ground features, has a wider application range and higher detection accuracy, and can be applied to the change detection of remote sensing images in different phases, the change detection of ground features before and after earthquakes, and the changes of ground features before and after floods The technical field of dynamic monitoring such as detection. Background technique [0002] Change detection on remote sensing images refers to the detection of changes in the area's features over time by inputting multiple remote sensing images of the same area at different times. It has become one of the most important application directions in the field of remote sensing image processing. It ha...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/40G06K9/46G06K9/62
CPCG06V20/13G06V10/30G06V10/44G06F18/23213G06F18/2135G06F18/24
Inventor 吕国敏刘昌军马强孙涛桑国庆于恒帅
Owner CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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