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SAR image denoising method based on contour wave domain block hidden Markov model

A Hidden Markov and Contour Wave technology, applied in the field of image processing, can solve the problems of lack of spatial adaptability and blurred edges of SAR images, and achieve the effect of overcoming spatial adaptability.

Active Publication Date: 2010-02-03
XIDIAN UNIV
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Problems solved by technology

However, the application of the CD-CHMM model to SAR image denoising lacks spatial adaptability, resulting in blurred edges

Method used

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  • SAR image denoising method based on contour wave domain block hidden Markov model
  • SAR image denoising method based on contour wave domain block hidden Markov model
  • SAR image denoising method based on contour wave domain block hidden Markov model

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Embodiment Construction

[0036] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0037] Step 1: Perform logarithmic transformation on the input SAR image, and convert the multiplicative noise into additive Gaussian white noise for processing: log y=log z+log x, where y represents the input SAR image, z represents the noise image, and x represents no Noise image; Contourlet decomposition is performed on the image after logarithmic transformation, in which the direction of the directional filter is 4, 4, 4, and the Contourlet transformation coefficient is obtained to obtain the high-frequency Contourlet coefficient.

[0038] Step 2: Establish an improved BlockHMM model in the Contourlet domain for the obtained high-frequency Contourlet coefficients, such as figure 2 shown.

[0039] The specific implementation is as follows:

[0040] (2a) The parent node between scales, sibling nodes between directions and neighborhood nodes within scale jointly determi...

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Abstract

The invention discloses a SAR image denoising method based on a contour wave domain block hidden Markov model, belonging to the field of image processing, mainly solving the problem of space adaptability shortage, serious detail information loss and fuzzy edge of current method, and comprising the following steps: (1) carrying out logarithmic transformation and Contourlet decomposition; (2) carrying out Block HMM modeling and training on a Contourlet coefficient; (3) correcting the Contourlet coefficient by estimation parameters; (4) carrying out Contourlet inverse transformation and antilogarithm transformation to the corrected Contourlet coefficient in order to obtain a one-time denoising image; (5) denoising a difference value image to obtain a second-time denoising image; and (6) fusing the one-time denoising image and the second-time denoising image and rotating and translating the fused image to obtain and output a final denoising image. The SAR image denoising method improves the space adaptability, reduces the calculation complexity and increases the edge resolution of the denoised image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for suppressing SAR image speckle noise, which can be used for denoising processing of SAR images, medical images and natural images. Background technique [0002] Synthetic aperture radar (SAR) has all-weather and all-weather earth observation capabilities, and can also obtain information through the surface and vegetation, playing an increasingly important role in military, remote sensing and other fields. The existence of speckle noise in SAR images seriously affects the accuracy of subsequent automatic interpretation and scene understanding tasks. Therefore, the removal of speckle noise is very important to the subsequent processing of SAR images. [0003] Speckle noise removal usually includes spatial filtering and transform domain methods. Spatial filtering such as Gamma-MAP to denoise SAR images can effectively reduce the influence of noise ...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/50G01S13/90
Inventor 焦李成侯彪田福苓王爽张向荣马文萍
Owner XIDIAN UNIV
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