Fast hyperspectral outlier detection method based on coarse localization and collaborative representation
A technology of collaborative representation and detection methods, applied in the field of remote sensing images, which can solve the problems of low detection accuracy and low efficiency.
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[0042] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0043] The present invention is a hyperspectral abnormal point rapid detection method based on rough positioning and cooperative representation, the flow chart is as follows figure 1 As shown, the specific steps are as follows:
[0044] Step 1. Perform spatial dimension degradation on the input hyperspectral remote sensing image;
[0045] Step 1 is specifically implemented according to the following steps:
[0046] Step 1.1, set the downsampling rate to 0.5, the corresponding upsampling rate to 2, and the corresponding upsampling methods are bicubic interpolation methods;
[0047] Step 1.2, downsampling the input original hyperspectral remote sensing image X according to the downsampling rate and method set in step 1.1;
[0048] Step 1.3. Upsampling the downsampled image in step 1.2 according to the upsampling rate and method set in step 1.1...
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