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Hidden Markov tree model based method for de-noising SAR image

An image and model technology, applied in the field of image processing, to achieve the effect of improving the equivalent visual number

Inactive Publication Date: 2012-06-20
XIDIAN UNIV
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Problems solved by technology

However, this model only captures the dependence in a small scale. When it is used for SAR image denoising, some details and texture information are smoothed, and the noise removal in the homogeneous area is not thorough enough, resulting in a low equivalent view number in the homogeneous area. Noise reduction is not ideal

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  • Hidden Markov tree model based method for de-noising SAR image

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Embodiment Construction

[0028] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0029] Step 1: Perform logarithmic transformation on the SAR image, and convert the multiplicative noise into additive Gaussian white noise for processing: logy=log z+log x, where y represents the input SAR image, z represents the noise image, and x represents the noise-free Image, using two sets of directional filters with different directions, the directions of the two sets of directional filters are 4, 4, 4 and 4, 8, 8 respectively, and performing Contourlet decomposition on the data after logarithmic transformation, the obtained Contourlet The transform coefficients are y 1 and y 2 .

[0030] Step 2: Transform coefficient y 1 Establish a one-way transfer HMT model, such as figure 2 As shown in (a), the black square is the parent node, and the four empty squares are its child nodes. The parameter set of the model is Θ 1 ; for transformation coefficient y 2 Establ...

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Abstract

The invention discloses a hidden Markov tree model based method for de-noising an SAR image, which relates to the field of image processing, and mainly solves the problems that details and texture information of an image are smoothed and an equivalent noise level in a homogeneous region is low. The method comprises the following steps: (1) carrying out logarithmic transformation and Contourlet decomposition; (2) carrying out HMT modeling on Contourlet coefficients, and training the model; (3) correcting the Contourlet coefficients by using estimated parameters; (4) establishing a background hidden Markov training model, correcting the coefficients again by using the estimated parameters, and carrying out Contourlet inverse transformation and exponential transformation to acquire a primaryde-noised image; (5) de-noising differential images to obtain a secondary de-noised image; and (6) combining the two de-noised images, and carrying out rotary translation on the combined image to acquire and output a final de-noised image. The method well maintains the details and texture information of the SAR image, reduces speckle noise in the homogeneous region of the SAR image, and can be used for de-noising the SAR image.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for denoising SAR images, which can be used for denoising SAR images, natural images and medical images. Background technique [0002] Synthetic aperture radar (SAR), as an active radar, has the characteristics of not being affected by light and weather conditions. It can observe the earth all-weather and all-weather, and can also obtain information through the surface and vegetation. It is used in agriculture, forestry, geology, environment, hydrology, Marine, disaster, surveying and mapping and military fields have been widely used. The existence of speckle noise in SAR images due to the coherent effect of scattering echoes from imaging scatterers is not conducive to the automatic analysis of scenes in images and the understanding of SAR images, making image interpretation difficult, especially for SAR images. The effect of point targets and edges is very no...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G01S13/90
Inventor 侯彪焦李成田福苓王爽张向荣马文萍
Owner XIDIAN UNIV
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