Space domain and frequency domain characteristic based parallel SAR (synthetic aperture radar) image classification method

A technology of frequency domain features and classification methods, applied in the field of information processing, can solve problems such as superficiality

Inactive Publication Date: 2015-07-01
薛笑荣 +2
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Problems solved by technology

However, our recent work on the parallel segmentation and classification of polarimetric SAR images is only a preliminary study, which is really superficial. The application of parallel computing in polarimetric SAR image segmentation and classification requires further in-depth research.

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  • Space domain and frequency domain characteristic based parallel SAR (synthetic aperture radar) image classification method
  • Space domain and frequency domain characteristic based parallel SAR (synthetic aperture radar) image classification method
  • Space domain and frequency domain characteristic based parallel SAR (synthetic aperture radar) image classification method

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Embodiment Construction

[0055] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so as to help understand the content of the present invention.

[0056] Such as figure 1 As shown, a parallel SAR image classification method based on spatial domain and frequency domain features, including the following steps:

[0057] S1, performing parallel denoising processing on the SAR image;

[0058] S2. Divide the original SAR image into n blocks according to the number of nodes, where n is the number of nodes;

[0059] S3. For each image, select an image block with a size of 8×8 pixels around each pixel;

[0060] S4, performing wavelet decomposition twice on the small image block to obtain seven wavelet sub-images;

[0061] S5. Calculate seven wavelet sub-image energy features and four gray level co-occurrence matrix features of each pixel in each image block respectively;

[0062] S6. Recover seven wavelet sub-image energy features ...

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Abstract

The invention provides a space domain and frequency domain characteristic based parallel SAR (synthetic aperture radar) image classification method. The method includes: by combining space domain and frequency domain characteristics of SAR images and based on the parallel computation environment, dividing the SAR images into n blocks prior to selecting a small image block in the size of 8*8 pixels around each pixel from each image block, computing corresponding wavelet energy features, gray-level co-occurrence matrix features and filtered gray-level average features of each pixel in each small image block, recovering the wavelet energy features, gray-level co-occurrence matrix features and filtered gray-level average features of each pixel in the n small image blocks to obtain wavelet energy features, gray-level co-occurrence matrix features and filtered gray-level average features of each pixel in the SAR images, forming the features into feature vectors for clustering, and finally classifying the SAR images. According to the method, quick classification of the SAR images depends on efficient information processing capability of a parallel cluster computer system, quick classification is realized, and the problem of low speed of SAR image classification in large data volume is solved.

Description

technical field [0001] The invention relates to the technical field of information processing, and relates to a SAR (Synthetic Aperture Radar) image processing method, in particular to a parallel SAR image classification method based on spatial domain and frequency domain features. Background technique [0002] SAR (Synthetic Aperture Radar) has important applications in national defense and national economic construction due to its unique all-weather, all-weather high-resolution imaging capabilities, and penetration detection of certain ground objects (such as in some large Earthquake disasters (such as the 2008 Wenchuan Earthquake and the 2010 Qinghai Yushu Earthquake) and flood disaster monitoring, disaster relief and post-disaster reconstruction, dynamic monitoring of drought and soil moisture, monitoring of agricultural diseases and insect pests, and monitoring of crop growth (there have been many studies at home and abroad, Successful examples of using radar data scatt...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 薛笑荣刘永革刘明亮王宏福向方宋东红薛骁勇彭金喜
Owner 薛笑荣
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