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Denoising Method of Synthetic Aperture Radar SAR Image Based on Parameter Estimation in Shear Wave Domain

A technology of synthetic aperture radar and parameter estimation, which is applied in image enhancement, image analysis, image data processing, etc., and can solve problems such as models that do not consider noise

Active Publication Date: 2018-12-11
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

However, the current algorithm based on the shear wave domain SAR image denoising, the coherent speckle noise is processed by a method similar to Gaussian noise removal after logarithmic processing, or the transformation coefficients are divided into three types: texture, edge and smooth area for processing Most of the methods do not consider the noise model

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  • Denoising Method of Synthetic Aperture Radar SAR Image Based on Parameter Estimation in Shear Wave Domain
  • Denoising Method of Synthetic Aperture Radar SAR Image Based on Parameter Estimation in Shear Wave Domain
  • Denoising Method of Synthetic Aperture Radar SAR Image Based on Parameter Estimation in Shear Wave Domain

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Embodiment Construction

[0029] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0030] The hardware environment used for implementation is: Intel (R) core (TM) i5-3230M computer, 4GB memory, and the software environment of operation is: Matlab7.0 and Windows 8. The method proposed by the present invention is realized with Matlab programming language. The image data adopts the method of adding multiplicative noise on the natural image to simulate the SAR image and a real image SAR image.

[0031] The present invention is specifically implemented as follows:

[0032] Step 1: Shearlet decomposition: perform shearlet decomposition on the SAR image containing multiplicative speckle noise to obtain the decomposed coefficient S, use L(S) to represent the low frequency approximation coefficient, and use Y(S) to represent the high frequency frequency detail factor;

[0033] Step 2: Parameter Estimation

[0034] 1) Estimate the noise variance σ an...

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Abstract

The invention relates to a synthetic aperture radar (SAR) image de-noising method based on shear wave domain parameter estimation. In coherent speckle filtering processing for SAR images, the statistics features of speckle noises are described by using Rayleigh distribution. Since the mathematic expression of a Laplace distribution model is simple, the estimated parsing solution can be obtained in combination with Bayes theory. For shear wave coefficients representing backward scattering components, Laplace distribution is used to present the probability density function of the shear wave coefficients. The experiment shows that the de-noising method based on shear wave parameter estimation has obvious suppression effect on coherent speckle noise in SAR images, and better retains edge texture information in the images.

Description

technical field [0001] The invention belongs to a SAR image denoising method based on shear wave domain parameter estimation, and relates to a synthetic aperture radar SAR image denoising method based on shear wave domain parameter estimation, which can be applied to single-view SAR images, and removes multiplied SAR images. Sexually coherent speckle noise. Background technique [0002] SAR (Synthetic Aperture Radar (SAR for short)) is a high-resolution imaging radar, which belongs to the active remote sensing system. Compared with other sensors, the penetration performance of ground objects can present more details, accurately determine the size of the target area, and better distinguish the characteristics of adjacent targets. However, the inherent coherent speckle noise of SAR images seriously reduces The degree of interpretability of SAR images is affected, which affects subsequent applications such as target detection, classification, recognition, and information extra...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10044
Inventor 杨宁路雅宁郭雷李晖晖
Owner NORTHWESTERN POLYTECHNICAL UNIV
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