Hyperspectral image classification method based on three-dimensional non-local mean filtering
A hyperspectral image, non-local mean technology, applied in the field of remote sensing image processing, can solve the problems of applying non-local mean filtering to hyperspectral data, increasing data processing time, and affecting the accuracy of classification
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[0029] The present invention will be further described below in conjunction with the accompanying drawings.
[0030] refer to figure 1 , the implementation steps of the present invention are as follows:
[0031] Step 1, input 3D hyperspectral image data with category labels.
[0032] 1.1) Input the three-dimensional hyperspectral image data to be classified and its category label. The hyperspectral image contains k categories in total, each category contains several pixels, and the size of the input hyperspectral image is m×n×d, where, d represents the total number of spectral bands of the hyperspectral image, m and n represent the number of rows and columns in the two-dimensional space, respectively, and N=m×n represents the total number of pixels;
[0033] 1.2) Express the pixel set of the hyperspectral image as X=[x 1 ,x 2 ,...,x s ,...,x N ], where x s Represents the pixel of the sth point after being arranged in two-dimensional spatial columns in the hyperspectral ...
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