Remote sensing image change detection method and device based on DT-CWT (dual-tree complex wavelet transform) and MRF (Markov random field)

A DT-CWT and change detection technology, applied in the field of image processing, can solve the problems of not considering pixel correlation, rough detection edges, sudden changes and weak expression of detail information

Active Publication Date: 2017-07-21
自然资源部国土卫星遥感应用中心
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Problems solved by technology

The threshold method is to distinguish the change and non-change pixels in the difference image by selecting an appropriate threshold, so as to obtain the final change area. Incomplete segmentation, while the detection results are heavily dependent on the chosen threshold
The transformation method is mainly a multi-scale transformation method, such as wavelet transformation. This type of method can perform multi-scale analysis and can better overcome the influence of factors such as sensor noise and registration error, but it does not consider the correlation between pixels. Rough edges, many false detection pixels
The image modeling method is to simulate the distribution information related to the spatial context by establishing a model. For example, the Markov Random Field (MRF) fully considers the

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  • Remote sensing image change detection method and device based on DT-CWT (dual-tree complex wavelet transform) and MRF (Markov random field)
  • Remote sensing image change detection method and device based on DT-CWT (dual-tree complex wavelet transform) and MRF (Markov random field)
  • Remote sensing image change detection method and device based on DT-CWT (dual-tree complex wavelet transform) and MRF (Markov random field)

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Embodiment Construction

[0062] The present invention is described more fully hereinafter, in which exemplary embodiments of the invention are illustrated.

[0063] Such as figure 1 Shown, the remote sensing image change detection method that the present invention proposes in conjunction with dual-tree complex wavelet transform (Dual-tree Complex WaveletTransform, DT-CWT) and Markov random field (MRF) comprises the following steps:

[0064] Step 1, input two grayscale images X corresponding to two precisely registered remote sensing images of the same area with the same size 1 、X 2 ;

[0065]Among them, the precise registration can be completed by the Registration module under the software ENVI Classic and by selecting the control points with the same name. The registration accuracy is less than one pixel. The change detection performed by the present invention is based on the two-phase remote sensing image change detection of pixels, so the change is performed Precise registration of images is req...

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Abstract

The invention discloses a remote sensing image change detection method and device based on DT-CWT (dual-tree complex wavelet transform) and MRF (Markov random field). According to the method and device of the invention, the multi-directional expression and multi-scale analysis of image information can be facilitated; correlations between pixels are fully utilized; the retention of high-frequency information and the removal of noises can be effectively balanced; edge detection is smoother; change detection results have good regional consistency; a false detection rate can be greatly reduced, and the influence of registration errors can be removed; and the accuracy of remote sensing image change detection can be greatly improved.

Description

technical field [0001] The invention relates to image processing technology, in particular to a remote sensing image change detection method and device combined with DT-CWT and MRF. Background technique [0002] With the continuous improvement of remote sensing data acquisition methods and the continuous shortening of update cycles, change detection technology, as an important application in remote sensing image processing and analysis, has been widely used in land use and land cover change monitoring, forest or vegetation change detection, and disaster relief. Governance, town and road changes, geographic database updates, and many other areas. Since the unsupervised change detection method can obtain the final change detection result without any additional prior knowledge except for the use of the two-temporal original image, the method is more efficient, so it has become a research hotspot. Usually unsupervised change detection is change detection based on pixel differen...

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Application Information

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IPC IPC(8): G06T7/00G06T7/10
Inventor 汪汇兵欧阳斯达唐新明史绍雨范奎奎张悦曹樱子叶芳宏
Owner 自然资源部国土卫星遥感应用中心
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