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SAR image speckle suppression method based on dictionary learning in wavelet domain

A technology of coherent speckle suppression and dictionary learning, applied in the field of image processing, it can solve the problems of image radiation distortion and edge blur, and achieve the effect of coherent speckle noise suppression and integrity assurance.

Active Publication Date: 2012-06-13
XIDIAN UNIV
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Problems solved by technology

The logarithmic transformation makes the processed image irradiance appear certain distortion, and the edge also appears certain blur

Method used

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  • SAR image speckle suppression method based on dictionary learning in wavelet domain
  • SAR image speckle suppression method based on dictionary learning in wavelet domain
  • SAR image speckle suppression method based on dictionary learning in wavelet domain

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Embodiment Construction

[0037] refer to figure 1 , the specific implementation process of the present invention is as follows:

[0038] Step 1. Input the SAR image Y to be speckle-reduced, and use the variance map method to divide the image Y into a smooth area pixel set Y ΩS and edge region pixel set Y ΩE , to get the smooth marker matrix S Y and edge labeling matrix E Y .

[0039] (1a) Let the pixel of the SAR image Y to be speckle reduced be expressed as y(i, j), and define each pixel of the variance map as:

[0040] V ( i , j ) = Σ m , n ∈ W [ y ( i , j ) - y ( m ...

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Abstract

The invention discloses a SAR (Synthetic Aperture Radar) image speckle suppression method based on dictionary learning in wavelet domain, which mainly solves the problems that the edge is not clear enough and the homogenous region is not smooth enough in the existing speckle reduction technology. The implementation process of the method comprises the following steps of: firstly, segmenting an original SAR image Y by a variogram method to obtain a smooth mark matrix SY and an edge mark matrix EY; performing N-level stationary wavelet transformation on the original SAR image Y to obtain sub-band images WY(s); modeling for a non-logarithmic additive noise in the WY(s) by zero-mean-value Guassian distribution; using an approximation KSVD (Singular Value Decomposition) algorithm to obtain a learner's dictionary D's and a sparse representative matrix Lambda's of each sub-band image WY(s), obtaining a reconstructed sub-band image according to the D's and the Lambda's, and obtaining an edge region of the sub-band images WY(s) by the edge mark matrix EY, and substituting the edge region in the reconstructed sub-band image to obtain modified sub-band images W'Y(s); performing inverse stationary wavelet transformation on the W'Y(s) to obtain the speckle- reduced image. The method has the advantages that the edge information after speckle reduction is complete and the homogenous region issmooth, and can be used for the pretreatment process of SAR image understanding.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for suppressing coherent speckles of SAR images, which can be used for interpretation and analysis of SAR images and image understanding preprocessing. Background technique [0002] SAR images are widely used in military and civilian fields. However, in the process of SAR imaging, due to the coherence of scatterer echoes, the image cannot truly reflect the scattering characteristics of ground objects. This interference phenomenon is called coherence speckle in SAR images. The existence of coherence speckle seriously affects the automatic interpretation of images and target recognition, and reduces the effectiveness and accuracy of image segmentation and target extraction. Therefore, it is very important to effectively suppress coherence speckle for the subsequent processing of SAR images. [0003] Spatial filtering is one of the main methods for SAR image speckl...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06T5/00G06T7/00
Inventor 焦李成侯彪蒋继光王爽刘芳尚荣华
Owner XIDIAN UNIV
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