Beta algorithm-based multiscale SAR (Synthetic Aperture Radar) image denoising method

An image noise reduction and multi-scale technology, applied in the field of SAR image noise reduction, can solve the problem of not keeping image edge information well, and achieve the effect of avoiding pseudo-Gibbs effect, ensuring integrity, and removing noise

Active Publication Date: 2013-05-01
XIDIAN UNIV
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Problems solved by technology

However, since these bases have specific directions, and a real image has various directions, the spars

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  • Beta algorithm-based multiscale SAR (Synthetic Aperture Radar) image denoising method
  • Beta algorithm-based multiscale SAR (Synthetic Aperture Radar) image denoising method
  • Beta algorithm-based multiscale SAR (Synthetic Aperture Radar) image denoising method

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Embodiment Construction

[0027] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0028] Step 1: Perform pixel classification on the SAR image I to be denoised to obtain edge image A, texture image B and homogeneous image C.

[0029] (1a) Input the SAR image I to be denoised, calculate the local variance map variance of the SAR image I to be denoised according to formula 1, and draw the local variance map variance histogram,

[0030] variance ( i , j ) = Σ ( y [ i , j ] y ‾ [ m ...

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Abstract

The invention discloses a Beta algorithm-based multiscale SAR (Synthetic Aperture Radar) image denoising method, mainly solving the problem that the conventional dictionary learning method is not applicable to SAR image denoising. The Beta algorithm-based multiscale SAR image denoising method comprises the steps of: carrying out pixel classifying on a to-be-denoised SAR image to obtain an edge image A, a texture image B and a homogenous image C; carrying out overlap block extraction and centralization on the images to obtain respective training sample sets; initializing a dictionary into a DCT (Discrete Cosine Transform) dictionary; carrying out sparse coding by using the dictionary to obtain a sparse coefficient matrix; updating kth line of the dictionary by using the sparse coefficient matrix; and repeating the sparse coding step and the dictionary updating step for K times to obtain a final dictionary and a final sparse coefficient matrix, and multiplying to obtain a denoised edge image A', a denoised texture image B' and a denoised homogenous image C', and further obtaining a denoised SAR image of I'=A'+B'+C'. The Beta algorithm-based multiscale SAR image denoising method has the advantages that the noise in the SAR image is effectively removed and texture and edge information of the image can be remained, and the method can be used in SAR image target recognition.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a SAR image noise reduction method, which can be applied to target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution radar system that can be used in many fields such as military affairs, agriculture, navigation, and geographic surveillance. It has many differences compared with other remote sensing imaging systems and optical imaging systems. In terms of military target recognition, SAR images are widely used in the field of target detection, and SAR image noise reduction is an important step from image processing to image analysis, and is the basis of target classification and recognition. In essence, the SAR image reflects the electromagnetic scattering characteristics and structural characteristics of the target, but since the SAR emits coherent electromagnetic waves, when it emits electromagnetic waves to the ground, the total ech...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 侯彪马晶晶陈芊芊焦李成张向荣马文萍
Owner XIDIAN UNIV
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