Method and device for classifying fully polarimetric synthetic aperture radar image

Abstract

The invention provides a method and a device for classifying a fully polarimetric synthetic aperture radar (SAR) image. The method comprises the following steps of: converting a covariance matrix of fully polarimetric SAR image data in a plural form into image data which is fully expressed by an intensive quantity; and classifying the fully polarimetric SAR image based on converted image data expressed by the intensive quantity. Thus, the fully polarimetric SAR image data which obeys different statistical distribution is converted into corresponding backscattering intensity image data which obeys uniform distribution, the conventional remote sensing image processing method based on the remote sensing image data which obeys the uniform distribution, such as an optical remote sensing image development-based partitioning method and an object-oriented classifying method, can be suitable for processing the fully polarimetric SAR image, and the classification accuracy of the fully polarimetric SAR image data is improved.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a method and device for classifying images of full polarization synthetic aperture radar. Background technique [0002] At present, many object-oriented remote sensing image processing methods have been developed. Among them, the multi-resolution image segmentation and object-oriented classification technology based on the development of optical remote sensing images are the most widely used. However, existing remote sensing image processing methods are generally applied based on the assumption that remote sensing image data obeys a uniform distribution, such as a Gaussian distribution. [0003] However, due to different imaging mechanisms, the synthetic aperture radar (SAR: Synthetic Aperture Radar) image data in remote sensing images obeys different statistical distributions, which leads to the statistical distribution of full-polarization SAR image data...

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Problems solved by technology

[0003] However, due to different imaging mechanisms, the synthetic aperture radar (SAR: Synthetic Aperture Radar) image data in remote sensing images obeys different statistical distributions, which leads to the statistical distribution of full-polarization SAR image data being different from the uniform distribution. Remote sensing image processing methods with data subject to uniform distribution, such as segmentation and object-oriented classification methods based on the development of optical remote sensing images, are not suitable for processing SAR image data, and there are cases where classification accuracy is reduced

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