Polarimetric SAR image classification method based on tensor MPCA

A classification method and image technology, applied in the field of image processing, can solve the problems of insufficient use of image information, multiple training samples, and degradation of classifier performance.

Active Publication Date: 2015-07-01
XIDIAN UNIV
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Problems solved by technology

However, the disadvantage of this method is that the original data needs to be converted into a vector form, which destroys the spatial structure information in the original data and does not make full use of image information, making this method require more training samples to train the classifier
However, the disadvantage of this method is that the noise immunity of this method is not strong, and the performance of the classifier decreases significantly when the noise is large.

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  • Polarimetric SAR image classification method based on tensor MPCA
  • Polarimetric SAR image classification method based on tensor MPCA
  • Polarimetric SAR image classification method based on tensor MPCA

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Embodiment Construction

[0042] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0043] Refer to attached figure 1 , the concrete steps of the present invention are as follows.

[0044] Step 1. Enter data.

[0045] Input the data of the three channels of polarimetric synthetic aperture radar image SAR, specifically including the horizontal emission and horizontal reception HH channel, the horizontal emission and vertical reception HV channel and the vertical emission and vertical reception VV channel, and the scattering intensity values ​​of the three channels.

[0046] Step 2. Data conversion.

[0047] Take a 3×3 neighborhood window for the pixels of each channel to obtain the feature matrix corresponding to each pixel, and then form the feature matrix of the corresponding pixel in the three channel data into a 3×3×3 third-order tensor as each A feature tensor of pixels.

[0048] Step 3. Extract image features.

[0049] Firstly, acc...

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Abstract

The invention discloses a polarimetric SAR image classification method based on a tensor MPCA, and the method can be applied to SAR image classification. The method includes 1, inputting data of three polarimetric SAR image channels; 2, converting original data into the tensor mode; 3, extracting image features; 4, training a classifier; 5, classifying the data to be classified, and acquiring the classification results. Since the data of the three polarimetric SAR image channels are converted into the tensor mode, the spatial structure information of the original data is utilized, and the classification accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a tensor MPCA-based polarization synthetic aperture radar (Synthetic Aperture Radar, SAR) image classification method in the technical field of target recognition. The invention can be used to classify different target areas in radar images. Background technique [0002] Radar is an active detection system that can work around the clock. It can penetrate a certain surface and change the frequency and intensity of emitted waves. Polarization SAR is a new type of radar used to measure echo signals. It can record the phase difference information of combined echoes in different polarization states, so it can obtain richer target information. It is used in agriculture, forestry, military, geology, hydrology and The ocean and other aspects have extensive research and application value, such as the identification of surface object types, disaster monitoring and assessmen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/66
Inventor 缑水平焦李成李鹏程马文萍马晶晶侯彪屈嵘
Owner XIDIAN UNIV
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