Polarimetric SAR image classification method based on feature attention and feature improvement network
A feature map and image technology, applied in the field of image processing, can solve problems such as complex model process, inability to learn and classify end-to-end, lack of consistency and accuracy, and achieve the effects of simplifying the process, improving classification accuracy, and enhancing consistency
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[0031] The present invention will be further described below in conjunction with the drawings and specific embodiments.
[0032] Reference figure 1 The implementation steps of the present invention are as follows.
[0033] Step 1: Input the polarization SAR image to be classified and filter the image to obtain the filtered polarization SAR image.
[0034] (1a) Input a polarization SAR image I to be classified with a size of h×p, where h and p represent the length and width of the image respectively;
[0035] (1b) Use an exquisite LEE filter method with a filter window size of 7×7 to filter the image I, remove the coherent speckle noise in I, and obtain the filtered polarized SAR image I'.
[0036] Step 2: Synthesize the pseudo color image of the polarized SAR image, and synthesize the classification label data of the polarized SAR image through the pseudo color image.
[0037] (2a) Perform Pauli decomposition on the scattering matrix S of each pixel in the filtered polarized SAR image I'.
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