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SAR image de-noising method based on NSCT domain edge detection and Bishrink model

An edge detection and image testing technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve problems such as easy loss of targets, errors in image processing and interpretation analysis, sacrifice of smooth performance, etc., to achieve effective image edges, Effects that preserve the edges of the image and remove the scratch effect

Inactive Publication Date: 2010-12-01
XIDIAN UNIV
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Problems solved by technology

This method uses wavelet technology to suppress speckle noise while maintaining edges to a certain extent, but at the expense of smoothing performance, the target in the image is easily lost, and it brings wrong results to subsequent image processing and interpretation analysis.

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  • SAR image de-noising method based on NSCT domain edge detection and Bishrink model
  • SAR image de-noising method based on NSCT domain edge detection and Bishrink model
  • SAR image de-noising method based on NSCT domain edge detection and Bishrink model

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Embodiment Construction

[0028] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0029] Step 1: Select the test SAR image I and perform non-subsampling contourlet transformation on it.

[0030] The present invention selects the mathematical model of testing SAR image as: y=x+n

[0031] Where y={y(i, j)|i, j=1, 2,...N} represents the SAR image, x={x(i, j)|i, j=1, 2,...N } represents the backscattering intensity of the real scene in the SAR image, n={n(i, j)|i, j=1, 2,...N} represents zero mean and variance equal to σ 2 Gaussian noise, N represents the size of the image;

[0032] Perform non-subsampling contourlet transformation on the selected test SAR image, and decompose the test SAR image into 6 layers of sub-band coefficients; y 1 is the coefficient of layer S, y 2 is the coefficient of layer S-1, S=3, 4, 5, 6.

[0033] Step 2: Keep the coefficients of the first layer and the second layer after the non-subsampled contourlet transformation of the ...

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Abstract

The invention discloses an SAR (Synthetic Aperture Radar) image de-noising method based on NSCT (Non-Subsampled Contourlet Transform) domain edge detection and a Bishrink model, mainly solving the problems of scratch effect and detail loss caused by carrying out the SAR image de-noising process by means of non-subsampled contourlet transform. The method comprises the following steps of: carrying out the non-subsampled contourlet transform on a selected SAR image and dividing the image into six layers of sub-band coefficients; keeping the first layer and the second layer of sub-band coefficients invariable and contracting the third to six layers of the sub-band coefficients by using the Bishrink model; reconstructing an image by means of non-subsampled contourlet inverse transform, and detecting an edge of the reconstructed image to carry out mean value filtering on the image subjected to the edge detection to obtain a filtered image; and carrying out non-linear anisotropism dispersion on a difference image obtained by subtracting the input image from the filtered image to obtain a de-noised image. The invention can excellently maintain edge information of the image and point target characteristic information, and can be used for interpretation analysis in the SAR image and pre-processing of image understand.

Description

technical field [0001] The invention belongs to the field of digital image processing, and relates to a denoising method for SAR images, which can be used for interpretation and analysis in SAR images and preprocessing for image understanding. Background technique [0002] SAR images have a very wide range of applications, but when SAR images are imaged, the scattered echoes of imaging scatterers have a coherent effect, making the images unable to effectively reflect the scattering characteristics of ground objects. This interference phenomenon is called speckle in SAR images. noise. Due to the coherence of the imaging system, SAR images are inevitably polluted by noise, which reduces the resolution of the image, hides the details of the image, and damages the quality of the image, causing great difficulties for target recognition and image interpretation. Therefore, it is very important to effectively suppress coherent speckle noise for the subsequent processing and interp...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
Inventor 侯彪焦李成贺富强张向荣王爽马文萍
Owner XIDIAN UNIV
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