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Level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and regional probability density difference

A probability density, image segmentation technique, applied in the field of image processing

Active Publication Date: 2011-02-16
XIDIAN UNIV
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Problems solved by technology

However, there are still few domestic studies on level set SAR image segmentation.

Method used

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  • Level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and regional probability density difference
  • Level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and regional probability density difference
  • Level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and regional probability density difference

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Embodiment Construction

[0047] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0048] Step 1: Apply the ROEWA edge detection operator to the segmented SAR image I to perform edge detection, and obtain the edge intensity modulus |R max |.

[0049] The specific process to realize this step is as follows:

[0050] (1a) Construct the causal filter f respectively 1 and non-causal filter f 2 as follows:

[0051] f 1 (z)=ab z H(z), f 2 (z)=ab -z H(-z);

[0052] Where z is the independent variable of the function, a and b satisfy a=1-b, 0-a <1, H(·) is a Heaviside function.

[0053] (1b) Construct an exponential smoothing filter f as follows:

[0054] f ( z ) = 1 1 + b f 1 ( z ) + b 1 + ...

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Abstract

The invention discloses a level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and a regional probability density difference, belonging to the technical field of image processing and mainly solving the problems of difficult segmentation of SAR images with fuzzy edges and inaccurate positioning to real edges of the SAR images, of the traditional level set method. The method comprises the following implementation steps of: firstly, detecting an edge intensity modulus absolute value of Rmax of an SAR image by applying an ROEW operator; secondly, initializing a level set function phi, segmenting the SAR image into an inner region omega1 and an outer region omega2, and solving for the intensity mean values c1 and c2 of the two regions; thirdly, solving for the estimated probability densities of the two regions omega1 and omega2 according to c1 and c2 and calculating the actual probability densities p1 and p2 of the two regions; and fourthly, constructing a total energy function ESAR, solving for a gradient downstream equation by applying a variational method, and updating the level set phi to obtain new segmentation regions omega1 and omega2. Indicated by experimental results, the segmentation method can be used for obtaining more ideal segmentation effect and be used for the edge detection and the target identification of the SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to applications in the field of SAR image segmentation, in particular to a level set SAR image segmentation method based on the combination of edges and regions, which can be used for SAR image segmentation, edge detection and target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution active radar with the advantages of all-weather, all-time, high resolution, and side-view imaging. It can be used in many fields such as military, agriculture, navigation, and geographic surveillance. SAR images are widely used in the field of target detection, and SAR image segmentation is an important step from image processing to image analysis, and is the basis of target classification and recognition. Since SAR is a coherent imaging system, the SAR image is essentially a response to the electromagnetic scattering characteristics and structural chara...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G01S13/90G06T7/00
Inventor 侯彪焦李成李书强王爽刘芳尚荣华
Owner XIDIAN UNIV
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