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SAR image edge detection method based on anisotropic morphology direction ratio

An anisotropy and image edge technology, applied in the field of image processing, can solve problems such as changes in statistical characteristics, difficulty in obtaining detection results, unfavorable ROA detectors to detect image edges, etc., to reduce the possibility, enhance continuity and smoothness , the effect of reducing the number of edge pixels

Active Publication Date: 2017-11-17
XIDIAN UNIV
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Problems solved by technology

However, there are more strong scattering points in the high-resolution SAR image. Although these strong scattering points provide finer target structure information, they are not conducive to the ROA detector to detect the edge of the image.
Since the appearance of strong scattering points increases the inhomogeneity of the SAR image, its statistical characteristics change, making it difficult for ROA detectors to obtain better detection results when processing SAR images containing strong scattering points

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  • SAR image edge detection method based on anisotropic morphology direction ratio
  • SAR image edge detection method based on anisotropic morphology direction ratio
  • SAR image edge detection method based on anisotropic morphology direction ratio

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[0033] Implementation rate and effect of the present invention are described in further detail below in conjunction with accompanying drawing:

[0034] refer to figure 1 , the implementation steps of the present invention are as follows:

[0035] Step 1, according to the input SAR image X, set the parameters of the Gaussian gamma double window.

[0036] The Gaussian gamma-shaped double window is a double window function symmetrically distributed along the center line, which is divided into the upper window W U and lower window W L , which obey the Gaussian distribution along the centerline direction, and obey the Gamma distribution perpendicular to the centerline direction, and its parameters include the Gaussian parameter σ in the x direction x , the gamma parameters α and β in the y direction;

[0037] In this example, when it is assumed that the center line of the Gaussian gamma double window is on the horizontal axis, the Gaussian gamma double window function of the pi...

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Abstract

The invention discloses an SAR image edge detection method based on the anisotropic morphology direction ratio, and mainly solves a problem that the edge detection is poor in robustness of discrete strong-scattering points in the prior art. carrying out the anticlockwise rotation of Gaussian gamma-shaped double windows, and carrying out the weighted median filtering of the Gaussian gamma-shaped double windows; calculating the multi-direction edge response through the median filtering, and carrying out the multi-direction edge response; calculating the edge intensity mapping according to the edge response; extracting a maximum value point from the edge intensity mapping as a candidate edge point; carrying out the double-threshold decision making of the candidate edge point, and obtaining an edge detection result of a final image. According to the invention, the method achieves the improvement of the robustness of the SAR image edge detection for discrete strong-scattering points, meets the real-time requirements of the SAR image edge detection in a large scene, and can be used for the extraction of the SAR image edge in the big scene comprising the discrete strong-scattering points.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a SAR image edge detection method, which can be used for image segmentation in large scenes containing sporadic strong scattering points. Background technique [0002] In recent years, with the continuous development of synthetic aperture radar (SAR) sensors, SAR image processing has gradually become a research hotspot in the field of SAR. Edge detection technology in the background of SAR images is a crucial research direction in the application technology of SAR image segmentation. Compared with traditional optical images, the human visual readability of SAR images is poor, and they are easily affected by coherence spots and deformations such as shortening of slopes, which makes the information processing of SAR images very difficult. The most prominent difficulty lies in SAR images are difficult to interpret, and most of the data is still interpreted manua...

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Application Information

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IPC IPC(8): G06T7/13G06T5/00
CPCG06T7/13G06T2207/10044G06T2207/20032G06T5/00
Inventor 水鹏朗聂源盈樊书辰许述文
Owner XIDIAN UNIV
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