Method and apparatus for detecting variation region of fully polarimetric SAR (Synthetic Aperture Radar) image

Abstract

The present invention discloses a method and apparatus for detecting a variation region of a fully polarimetric SAR (Synthetic Aperture Radar) image. The method comprises: using a multi-look polarimetric SAR multiplicative model based on an extremely uneven texture to carry out fitting on fully polarimetric primary and secondary SAR images received successively, so as to separately obtain texture images and spot noise covariance images of the primary and secondary SAR images, and determining corresponding distribution parameters of probability density functions according to the texture images of the primary and secondary SAR images, wherein the primary and secondary SAR images are high-resolution fully polarimetric SAR images covering a same object region; according to the respective texture images, spot noise covariance images, and distribution parameters of the probability density functions of the primary and secondary SAR images and by means of similarity measurement of the multi-look polarimetric SAR multiplicative model based on the extremely uneven texture, comparing the primary and secondary SAR images to obtain difference information, and on the basis of the difference information, determining a difference image relative to the primary and secondary SAR images; and comparing the difference image with the primary and secondary SAR images to detect a variation region.

Description

technical field [0001] The invention relates to a method and a device for detecting a change area of ​​a fully polarized SAR image. Background technique [0002] Since the beginning of the 21st century, the world's population has increased rapidly, land desertification has gradually become serious, resources have become increasingly scarce, and natural disasters have occurred frequently. The Wenchuan earthquake in 2008, the Yushu earthquake in Qinghai in 2010 and the catastrophic Indonesian tsunami in 2011, the Fukushima earthquake in Japan in 2011, and the typhoon "Haiyan" in 2013 have repeatedly aroused the attention of all mankind to remote sensing in disaster monitoring and assessment. In practical applications, most of the above monitoring problems are proposed in the form of change detection, that is, through observations at different time periods, to identify the change process of the state of urban, forest, water, farmland and other ground objects. Radar earth obser...

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Problems solved by technology

[0007] The problem to be solved by the present invention is that the existing fully polarimetric SAR model cannot provide accurate regional change areas, and a multi-view polarization SAR multiplicative model based on extremely uneven texture can detect accurate change areas

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