Polarized SAR (synthetic aperture radar) image segmentation method with space adaptivity

An image segmentation and adaptive technology, applied in the field of image processing, can solve problems such as lack of spatial adaptability, poor segmentation effect, and no consideration of changes in scene complexity

Active Publication Date: 2012-10-10
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

This method has high segmentation accuracy, fewer isolated pixels in the segmentation result, and better image connectivity, but its shortcomings are also very obvious.
This method does not consider the change

Method used

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  • Polarized SAR (synthetic aperture radar) image segmentation method with space adaptivity
  • Polarized SAR (synthetic aperture radar) image segmentation method with space adaptivity
  • Polarized SAR (synthetic aperture radar) image segmentation method with space adaptivity

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0044] The experimental data are the multi-view full-polarization SAR images of the Flevoland area in the Netherlands acquired by the NASA-JPL airborne L-band AIRSAR system in 1991, such as figure 2 . This image is widely used in polarization SAR image segmentation and classification experiments. The size of the image is 320*400, mainly composed of 6 types of crop areas, and the rest are unknown crop areas. The image according to the present invention figure 1 The process shown is processed, and the specific steps are as follows:

[0045] Step 1 as figure 1 In S11, Lee filtering is performed on the image to reduce coherent speckle noise. The filtering window is a rectangular window with a size of 3*3;

[0046] Step 2, initial clustering, the filtered image obtained in step 1 is processed as follows:

[0047] Step 2-1 as figure 1 In S121, H / α cl...

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Abstract

The invention provides a polarized SAR (synthetic aperture radar) image segmentation method with space adaptivity, mainly solving the problem that a segmentation result can not reflect image detail information caused by insufficient space complexity adaptivity by using the conventional segmentation technique. The polarized SAR image segmentation method comprises the following steps of: firstly, combining H/alpha-ML Wishart cluster and quadtree disassemble to obtain initial segmentation areas with unequal sizes and capability of adapting scene complexity, and regulating the sizes and the shapes of the initial segmentation areas by utilizing complex Wishart distribution and an MRF (markov random field) to obtain a final segmentation result. The method fully and effectively utilizes polarization information of a polarization SAR image with the excellent space adaptivity, the segmentation result can be used for well reserving detail information of a polarization SAR image, the segmentation speed is relatively quick and the segmentation result is relatively exact.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to a space-adaptive polarization synthetic aperture radar (SAR) image segmentation method. Background technique [0002] Compared with the traditional synthetic aperture radar (SAR), polarimetric SAR uses the scattering information of multiple channels to obtain a more comprehensive understanding of the target. After decades of development, great progress has been made in the theoretical and applied research of polarimetric SAR. Various polarimetric SAR system platforms have acquired a large amount of ground data, and the analysis and interpretation of these multi-polarimetric data has become an important task in recent years. Research hotspots. Image segmentation is just one of the key steps. Due to the serious influence of coherent speckle noise, the segmentation of polarimetric SAR images is very difficult. Edge detection-based methods and pixel clustering-based methods ...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 胡昊柳彬周雨浩浮瑶瑶于秋则刘兴钊郁文贤
Owner SHANGHAI JIAO TONG UNIV
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