Polarized SAR (Synthetic Aperture Radar) image classification method based on SLIC (Software Licensing Internal Code) and improved CNN (Convolutional Neural Network)

A classification method and image technology, which is applied in the field of image processing, can solve the problems of slow classification speed and low classification accuracy, achieve the effects of saving memory, improving classification accuracy, and avoiding a large number of repeated calculations

Active Publication Date: 2017-05-31
XIDIAN UNIV
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Problems solved by technology

[0011] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, propose a kind of polarimetric SAR image classification method based on improved C

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  • Polarized SAR (Synthetic Aperture Radar) image classification method based on SLIC (Software Licensing Internal Code) and improved CNN (Convolutional Neural Network)
  • Polarized SAR (Synthetic Aperture Radar) image classification method based on SLIC (Software Licensing Internal Code) and improved CNN (Convolutional Neural Network)
  • Polarized SAR (Synthetic Aperture Radar) image classification method based on SLIC (Software Licensing Internal Code) and improved CNN (Convolutional Neural Network)

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[0036] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0037] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0038] Step 1. According to the nine-dimensional polarization data T of the polarization SAR image, calculate the Wishart distance of each pixel in the polarization SAR image, and combine the distance with the nine-dimensional polarization data T to obtain new data of the polarization SAR image. The steps are:

[0039] (1a) Input the category labels of the nine-dimensional polarization data of the polarimetric SAR image, and select the adjacent samples of each category of labels to obtain multiple categories of polarization samples.

[0040] (1b) Calculating the coherence matrix mean C of each class of polarized samples i , where i is the number of categories the sample belongs to.

[0041](1c) Using the coherence matrix mean value C i , calculat...

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Abstract

The invention puts forward a polarized SAR (Synthetic Aperture Radar) image classification method based on an SLIC (Software Licensing Internal Code) and an improved CNN (Convolutional Neural Network), and is used for solving the technical problem of low classification speed and low classification accuracy in an existing supervised polarized SAR image classification method. The method comprises the following steps that: firstly, taking the Wishart distance and the polarization feature of a polarized SAR image as new data, carrying out Lee filtering on the new data, and inputting the new data into an improved CNN to be classified so as to obtain a preliminary classification result; then, carrying out SLIC superpixel segmentation on the pseudo-color image of the polarized SAR image to obtain a superpixel segmentation result; and finally, utilizing the superpixel segmentation result to carry out constraint post-processing on the preliminary classification result to obtain a final classification result. The method is high in classification speed and accuracy, and can be used for fields including polarized SAR terrain classification and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a polarimetric SAR image classification method, in particular to a polarimetric SAR image classification method fused with SLIC and an improved CNN, so that the convolutional neural network model can quickly perform polarimetric SAR data Accurate classification can be applied to ground object classification, target detection and target recognition of polarimetric SAR images. Background technique [0002] Image classification technology mainly uses the different features reflected in the image information to quantitatively analyze the image and attribute it to a certain category. The SAR image acquisition method is different from the natural image, which uses the relative motion between the imaged ground target and the radar to improve the azimuth resolution of the radar image. Each pixel of the SAR image contains not only the gray value reflecting the surface microwave re...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24G06F18/214
Inventor 王爽焦李成孟龙祥樊伟明赵阳张妍妍梁雪峰
Owner XIDIAN UNIV
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