High-resolution SAR image classification method based on depth ladder network

A classification method and high-resolution technology, applied in the field of image processing, can solve problems such as time-consuming and unreliable images, and achieve the effect of reducing training data, reducing test time, and improving classification speed and accuracy

Active Publication Date: 2017-09-05
XIDIAN UNIV
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Problems solved by technology

However, manual labeling is time-consuming, and the labeled im

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  • High-resolution SAR image classification method based on depth ladder network
  • High-resolution SAR image classification method based on depth ladder network
  • High-resolution SAR image classification method based on depth ladder network

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] refer to figure 1 , the specific implementation steps of the high-resolution SAR image classification method based on the depth ladder network of the present invention are as follows:

[0047] Step 1, input the high-resolution SAR image to be classified, and its artificially labeled image; construct the training data set D1 and the test data set D2 from the high-resolution SAR image and its labeled image, and select the German DLR for the high-resolution SAR image to be classified The horizontal polarization map of the X-band tri-polarization data acquired by the ESAR sensor in Traunstein County, the image resolution is 1 meter, and the image size is 4278×6187 pixels;

[0048] Specific steps are as follows:

[0049] (1a) First, three times downsampling is performed on the original image of the high-resolution SAR image, and then a block with a size of 21×21 pi...

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Abstract

The invention discloses a high-resolution SAR image classification method based on a depth ladder network, mainly to solve the problem that the high-resolution SAR image has few data with class identifiers and a network can not be trained effectively. The method comprises steps: a to-be-classified high-resolution SAR image and identifier information thereof are inputted; a training data set D1 and a test data set D2 are constructed; features of the data sets D1 and D2 are normalized to obtain data sets D3 and D4; a classifier model based on the depth ladder network is constructed; the training data set D3 is used for training the network; and the well-trained classifier model is used for classifying the test data set D4. The few training samples with class identifiers can be made full use of, and the high classification precision can be acquired.

Description

[0001] 【Technical field】 [0002] The invention belongs to the technical field of image processing, and in particular relates to a high-resolution SAR image classification method based on a deep ladder network, which can be used in target detection and ground object classification methods. [0003] 【Background technique】 [0004] Synthetic Aperture Radar (SAR) is widely used in the field of earth science remote sensing, because it not only has all-day and all-weather characteristics, but also provides different information than infrared and visible light sensors. Therefore, the understanding and interpretation of SAR images has become a research hotspot. [0005] SAR image surface object classification is the application of pattern classification in SAR image processing. It completes the work of converting the image from the two-dimensional gray space to the target pattern space. The result of the classification is to divide the image into multiple different categories accordin...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/08G06T7/11
CPCG06N3/08G06T7/11G06T2207/20021G06F18/285G06F18/214
Inventor 焦李成屈嵘李晰张丹杨淑媛侯彪马文萍刘芳尚荣华张向荣唐旭马晶晶
Owner XIDIAN UNIV
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