POLSAR image unsupervised classification method based on target scattering identification

A technology of target scattering and classification method, which is applied in the field of unsupervised classification of POLSAR images based on target scattering identification, which can solve the problems of unreasonable assumptions, reduced algorithm practicability, and too large algorithm calculation amount.

Inactive Publication Date: 2012-11-28
SUN YAT SEN UNIV
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However, the premise of this method is that the POLSAR image obeys the Wishart distribution, which is usually unreasonable due to the complexity of the actual scene
At the same time, in the process of cat

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  • POLSAR image unsupervised classification method based on target scattering identification
  • POLSAR image unsupervised classification method based on target scattering identification
  • POLSAR image unsupervised classification method based on target scattering identification

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[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0032]Aiming at the deficiencies in the existing unsupervised classification of ground objects in POLSAR images, the present invention proposes a new unsupervised classification method for POLSAR images based on target count identification. The method is divided into two parts: scatter classification and class adjustment. Since the new method automatically determines the scattering category of ground objects according to the similarity parameters of surface scatter...

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Abstract

The invention provides a POLSAR image unsupervised classification method based on target scattering identification. The POLSAR image unsupervised classification method comprises the steps of: 1, calculating a POLSAR image polarization scattering entropy and similarity parameters of surface scattering, even time scattering and volume scattering and initially dividing classes of POLSAR images by using the parameters; 2, selecting the minimum antenna receiving power characteristic polarization of surface features mainly referring to surface scattering, and with the minimum antenna receiving power characteristic polarization as an antenna polarization state, calculating an antenna receiving power of each pixel; 3, calculating the center of each class; 4, calculating a polarization scattering difference measurement of each pixel, judging the pixel as a class with the minimum difference measurement; and 5, checking whether the ending condition is reached, and if not, returning the step 4. According to the POLSAR image unsupervised classification method based on target scattering identification, the scattering of the ground features can be more accurately described and can well correspond to the actual scattering condition of the ground features, thus the operation time of class regulation is reduced.

Description

technical field [0001] The invention relates to the technical field of image classification, in particular to an unsupervised classification method for POLSAR images based on target scattering identification. Background technique [0002] Polarization Synthetic Aperture Radar (POLSAR) has become the most promising remote sensing device today because of its high-resolution, all-weather, wide-range imaging capabilities, and the ability to obtain complete target information characterization data. Nowadays, with the continuous emergence of various spaceborne and airborne POLSAR systems, the number of POLSAR images is increasing rapidly. How to quickly and accurately interpret these image data will be a hot issue of general concern in the field of remote sensing in the future. [0003] POLSAR image classification is an important research content of POLSAR image interpretation. According to whether there is manual intervention in the classification process, POLSAR image classific...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 陈子琦罗笑南陈湘萍林谋广
Owner SUN YAT SEN UNIV
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