An Object-Oriented Algorithm for Change Detection in Multispectral High Resolution Remote Sensing Images
A change detection, object-oriented technology, applied in the field of optical remote sensing image change detection, can solve the problems of efficiency and accuracy limitations, without considering object correlation, etc., and achieve the effect of reliable change detection results and improved accuracy
Active Publication Date: 2021-11-30
HOHAI UNIV
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However, this method is based on pixels, and the detection efficiency and accuracy have certain limitations.
The object-oriented chi-square transform-based detection method (OBCT) proposed by B.Desclée et al. can overcome the limitations of pixel-based change detection, but the object-oriented method does not consider the correlation between objects
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[0064] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.
[0065] refer to figure 1 , the realization steps of the present invention are as follows:
[0066] Step 1: Input two high-resolution optical remote sensing images of the same area and different time phases, denoted as: X 1 and x 2 .
[0067] Step 2: use the remote sensing software ENVI to measure X 1 and x 2 Image registration is divided into two steps: rough correction and fine correction:
[0068] For geometric rough correction, use the relevant functions in ENVI4.8 software to realize, the specific operation steps are: (1) display the reference image and the image to be corrected; (2) collect ground control points GCPs; GCPs should be evenly distributed in the entire image , the number of GCPs is at least greater than or equal to 25. (3)...
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The invention discloses an object-oriented CRF-based multi-temporal multi-spectral remote sensing image change detection method, comprising the following steps: inputting two high-resolution optical remote sensing images of the same area and different temporal phases; 1 and x 2 Carry out image registration, which is divided into rough correction and fine correction; use multivariate change detection MAD method to X 1 and x 2 Carry out radiation normalization correction; segment based on SLIC algorithm; calculate difference images of multi-temporal images, and use FCM algorithm for clustering; construct CRF multi-neighborhood system based on SLIC segmented images, and construct CRF binary term energy; The cyclic belief propagation LBP optimization algorithm optimizes the CRF energy item U to obtain the final change detection result. The invention makes the change detection result more reliable and robust.
Description
technical field [0001] The invention relates to an object-oriented multi-temporal, multi-spectrum, high-resolution remote sensing image non-supervised change detection method based on conditional random field CRF, and belongs to the technical field of optical remote sensing image change detection. Background technique [0002] With the continuous accumulation of multi-temporal remote sensing data and the successive establishment of spatial databases, how to extract and detect change information from these remote sensing data has become an important research topic in remote sensing science and geographic information science. According to remote sensing images of different time phases in the same area, dynamic information such as cities and environments can be extracted to provide scientific decision-making basis for resource management and planning, environmental protection and other departments. [0003] Change detection of remote sensing images is to quantitatively analyze ...
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IPC IPC(8): G06T7/00G06T7/10G06T7/30
CPCG06T7/0002G06T2207/10032G06T7/10G06T7/30
Inventor 石爱业王维王鑫马贞立
Owner HOHAI UNIV