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A thresholded image denoising method based on non-subsampled contourlet transform

A non-subsampling, image technology, applied in the field of thresholding image denoising based on non-subsampling Contourlet transform, can solve problems such as interference, Contourlet transform has no translation invariance, affects image quality, etc., and achieves high peak signal-to-noise ratio, The image edge and texture details are clear, and the effect of improving the denoising effect

Inactive Publication Date: 2017-10-03
HOHAI UNIV
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Problems solved by technology

However, because the Contourlet transform is not translation invariant, the processed image is disturbed by the pseudo-Gibbs phenomenon, which seriously affects the quality of the processed image.

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  • A thresholded image denoising method based on non-subsampled contourlet transform
  • A thresholded image denoising method based on non-subsampled contourlet transform
  • A thresholded image denoising method based on non-subsampled contourlet transform

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Embodiment Construction

[0045] Below in conjunction with accompanying drawing, technical scheme is described in detail:

[0046] Such as figure 1As shown, the thresholded image denoising method based on non-subsampling Contourlet transform provided by the present invention specifically includes the following steps:

[0047] Step 1: Select the test object, add Gaussian noise, and get the noise image;

[0048] Step 2: Build a model for NSCT of noisy images: in, Respectively represent the noisy image, the original image and the noise after NSCT, when the scale is k, the coefficient in the j-th direction, k=0,1,...,K-1; j=0,1,...J-1, K is NSCT The total number of scales for decomposition, J is the number of directions for decomposition at the kth layer. Perform a three-layer non-subsampling Contourlet transform on the noisy image. According to the order of the scale from coarse to fine, the number of direction subbands is 8, 8, and 16, and the subband coefficients on the kth scale and jth direction...

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Abstract

The invention discloses a thresholding image denoising method based on non-subsampling Contourlet transform, which mainly solves the problem of poor effect of the existing denoising methods. The implementation process is: 1) input a noisy image; 2) perform non-subsampling Contourlet transform on the noisy image; 3) estimate the noise variance of each subband and the coefficient standard deviation in the transform domain; 4) set reasonable 5) Threshold the NSCT coefficients using the improved semi-soft threshold function, and do not process the low-frequency components; 6) Perform non-subsampling Contourlet inverse transformation on the processed NSCT coefficients to obtain the denoised image. The invention can effectively remove the noise in the natural image containing Gaussian white noise, and while removing the noise, the edge of the image information is preserved as much as possible, so as to obtain the best restoration of the original image, and has a good application prospect and great development. potential.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to a thresholding image denoising method based on non-subsampling Contourlet transform. Background technique [0002] Image denoising is a very important research field in image processing. One of the problems is to remove the noise while trying not to destroy the information of the original image. Therefore, the ideal image denoising needs to achieve two goals: the first maximum Suppress noise; the second is to preserve the detailed feature information of the image as much as possible. The traditional noise reduction method largely removes the noise of the image, and also removes the useful high-frequency information of the image part. With the development of wavelet transform, image denoising using wavelet transform has become an active research topic. The multi-scale geometric analysis developed in recent years has also become a favorable tool for image denoisin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 汪飞陈亮曹宁鹿浩毛明禾胡一帆
Owner HOHAI UNIV
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