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Self-adaptive de-noising and characteristic enhancing method of SAR (Synthetic Aperture Radar) image

A feature enhancement and self-adaptive technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of non-adaptive selection of parameters, poor noise resistance, etc., and achieve the effect of reducing complexity and good noise resistance.

Inactive Publication Date: 2010-11-10
HAIAN TEXTILE MACHINERY +1
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Problems solved by technology

[0005] In order to overcome the shortcomings of poor anti-noise performance of existing methods and the inability to adaptively select parameters in experiments, the present invention proposes a SAR image adaptive denoising and feature enhancement method, using mirror-extended curvelet (Mirror-Extended curvelet, ME-curvelet) transformation Combined with improved particle swarm optimization (Particle Swarm Optimization, PSO) algorithm for adaptive denoising and feature enhancement

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  • Self-adaptive de-noising and characteristic enhancing method of SAR (Synthetic Aperture Radar) image
  • Self-adaptive de-noising and characteristic enhancing method of SAR (Synthetic Aperture Radar) image
  • Self-adaptive de-noising and characteristic enhancing method of SAR (Synthetic Aperture Radar) image

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Embodiment Construction

[0053] Referring to the attached picture:

[0054] 1. Take the logarithm of the input SAR image gray value matrix. Input a SAR image f, and perform logarithmic transformation on it, so that the multiplicative coherent speckle noise is transformed into approximate Gaussian additive noise, and the logarithmic image f′ is obtained.

[0055] 2. Perform ME-curvelet forward transformation on the logarithmic image f', and obtain the ME-curvelet coefficient matrix c in different directions l under different decomposition scales j jl (j=1, 2,..., J, J is the maximum decomposition scale, l=1,..., L j , L j is the number of directions under the jth scale).

[0056] 3. Using the improved PSO algorithm to optimize each parameter in the improved gain function, and obtain the optimal value of each parameter in the improved gain function.

[0057] The improved gain function adopted in the present invention is an improved gain function that integrates denoising and feature enhancement, nam...

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Abstract

The invention discloses a self-adaptive de-noising and characteristic enhancing method of an SAR (Synthetic Aperture Radar) image, which mainly aims at overcoming the defects that the traditional method has poor de-noising property and can not self-adaptively select parameters in the experiment. The method comprises the following steps: firstly, carrying out logaritmim and then ME-curvelet transformation on an original SAR image; secondly, self-adaptively selecting and optimizing parameters in improved gain functions by adopting an improved PSO (Particle Swarm Optimization) algorithm according to the provided evaluation criterion; and finally, carrying out the nonlinear transformation on ME-curvelet coefficients, ME-curvelet inverse transformation and exponential transformation by adopting the improved gain functions to obtain the final SAR image subjected to the de-noising and characteristic enhancement. By using the method, the noise can be removed while the characteristics are enhanced, the complexity for processing can be reduced and the better de-noising and characteristic enhancing effects of the SAR image can be achieved.

Description

technical field [0001] The invention relates to a SAR image adaptive denoising and feature enhancement method. Background technique [0002] The coherence of Synthetic Aperture Radar (SAR) imaging system makes speckle noise an inherent defect of SAR images, so it is of great significance to suppress the coherent speckle noise of SAR images and enhance the target of interest. The existing SAR image enhancement methods mainly include spatial domain methods such as histogram equalization and unsharp masking, and frequency domain methods that enhance the frequency components of interest through Fourier transform. While these methods enhance the image contrast, they also amplify the noise, so that the detailed information of the SAR image is overwhelmed by the noise. The wavelet transform enhancement algorithm is a widely popular image enhancement method in recent years, but the latest research shows that due to the isotropic characteristics of the wavelet base, it can only refl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 李映龚红丽张艳宁
Owner HAIAN TEXTILE MACHINERY
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