Non-supervision and Fourier kernel function based remote sensing image pixel purity identification method
A technology of remote sensing images and identification methods, applied in image analysis, image data processing, instruments, etc., can solve problems such as low accuracy and inconvenient application
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[0071] The present invention is described in detail below in conjunction with accompanying drawing:
[0072] Such as figure 1 As shown, the present invention provides a remote sensing image pixel purity recognition method based on unsupervised and Fourier kernel function, comprising the following steps:
[0073] S1, read the original remote sensing image; wherein, the original remote sensing image is composed of M*N pixels in M rows and N columns, and the pixel set is S={S 1 , S 2 ,...,S M×N};
[0074] S2. Segment the original remote sensing image to obtain P relatively independent objects with a size greater than or equal to 1 pixel, expressed as: V={V 1 , V 2 ,...,V P};
[0075] In this step, the image segmentation of the original remote sensing image can be performed based on the maximum a posteriori probability criterion by using the Markov random field image module.
[0076] What needs to be emphasized is that in the subsequent steps, the present invention takes...
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Abstract
Description
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