Remote sensing image change detection method based on chi-square transformation and sample selection

A remote sensing image and change detection technology, which is applied in the field of remote sensing science and technology, can solve problems such as the small area of ​​the changed area and the unchanged area, and the inability to obtain the change threshold

Active Publication Date: 2016-07-06
北京图迅丰达信息技术有限公司
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Problems solved by technology

However, geographical national conditions monitoring covers a large geographical area and requires the use of large-format remote sensing images. When the time interval between the two time-phase remote sensing images is short,

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  • Remote sensing image change detection method based on chi-square transformation and sample selection
  • Remote sensing image change detection method based on chi-square transformation and sample selection
  • Remote sensing image change detection method based on chi-square transformation and sample selection

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Embodiment Construction

[0040] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0041] please see figure 1 , a kind of remote sensing image change detection method based on chi-square transformation and sample selection provided by the present invention comprises the following steps:

[0042] Step 1: Register the remote sensing image T2 to the image T1 with respect to the large format by using the registration method of differential correction of small bins;

[0043] Step 2: Perform multi-scale segmentation on the registered large-format remote sensing images in different phases to obtain image spots;

[0044] The fractal network evoluti...

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Abstract

The invention discloses a remote sensing image change detection method based on chi-square transformation and sample selection. Multi-scale segmentation is performed on a multi-temporal remote sensing image so as to obtain image spots; the multi-dimensional features of the image spots are extracted, and the weighted difference degree of the image spots is calculated by adopting a feature fusion method based on chi-square transformation; and training samples are self-adaptively selected, a change threshold is obtained through a Bayes threshold determination method based on an expectation maximization algorithm, and binary segmentation is performed on the weighted difference image so as to obtain a change detection result. The correct rate of change detection is ensured to be high and leak detection is also effectively reduced so that the better change detection result is obtained. The remote sensing image change detection method has great application value in monitoring of the surface coverage change.

Description

technical field [0001] The invention belongs to the field of remote sensing science and technology, and relates to a remote sensing image change detection method, in particular to an object-oriented remote sensing image change detection method based on chi-square transformation and sample selection. Background technique [0002] Due to the increasing application of high-resolution remote sensing images, object-level change detection, which can take advantage of its advantages, has gradually replaced pixel-level change detection and become the mainstream change detection technology. The object is a homogeneous collection of pixels, which can also be called an image spot. The image spot contains multi-dimensional features, and the change detection method based on the difference method or the ratio method uses a single feature for change detection, which cannot fully express the information of the image spot. Although the change detection based on the ChangeVectorAnalysis (CVA...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T2207/10032
Inventor 贾永红谢志伟
Owner 北京图迅丰达信息技术有限公司
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