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In order to resolve the problem that the denoising performance has a sharp drop when noise standard deviation reaches 40, proposed to replace the wavelet transform by the DCT. In this comment, we argue that this replacement is unnecessary, and that the problem can be solved by adjusting some numerical parameters. We also present this parameter modification approach here. Experimental results demonstrate...
In order to solve the problem of weakening the details and the edges of image while denoising in the contourlet domain, this paper presents an adaptive denoising algorithm with detail enhancement and applies it to the denoising procedure of infrared image. On the basis of the assumption that the prior distribution of the original image coefficients and the noise's are both Gaussian in the contourlet...
Synthetic Aperture Radar (SAR) images compression is very important in reducing the burden of data storage and transmission in relatively slow channels. The relatively new transform of multiwavelets can possess desirable features simultaneously such as short support, orthogonality and symmetry, while scalar wavelets cannot. And the Spatial Orientated Tree (SOT) is an efficient data structure to investigate...
A symmetrical second-generation wavelet named zzxb7.9 with two vanishing moments was constructed according to the lifting scheme introduced by Sweldens etc. and used for image denoising. Simulated noise images are used to evaluate the denoising performance of the second-generation wavelet zzxb7.9. The experimental results show that the second-generation wavelet zzxb7.9 is to be promising in image...
The performance of various estimators, such as minimum mean square error (MMSE) is strongly dependent on correctness of the proposed model for original data distribution. Therefore, the selection of a proper model for distribution of wavelet coefficients is important in wavelet based image denoising. This paper presents a new image denoising algorithm based on the modeling of wavelet coefficients...
We propose a new method for image denoising based on contourlet-domain hidden Markov tree (CHMT) models, which have been recently introduced. CHMT models achieve superior denoising results over wavelet-domain HMT (WHMT) models in terms of visual quality. But denoising by means of CHMT still introduces some artifacts due to the lack of translation invariance of the contourlet transform. We employ a...
We propose a new local adaptive shrinkage denoising approach based on the neighborhood characteristics of contourlet coefficients. Classical contourlet shrinkage denoising methods process the contourlet coefficients with a fixed threshold in each subband, without considering the clustering property of the coefficients. The shrinkage denoising method proposed in this paper determines the shrinkage...
A new system of multiscale transform, namely, the curvelets, was developed recently, which possess directional features and provides optimally sparse representation of objects with edges. In this paper a novice algorithm for image denoising based on lossy compression and curvelet thresholding(LCCT) is proposed. The results are compared with the results obtained from denoising methods like Wavelets(WDT),...
In this paper, a new method of de-noising, using complex Daubechies wavelet (CDW) transform, has been proposed and applied to on-site noise rejection for UHF PD measurements. It is a relatively recent enhancement to the real-valued wavelet transform because of the important properties, which are nearly shift-invariant and availability of phase information. Those properties give CDW transform superiority...
With the wide spread of video usage in many fields of our lives, it becomes very important to develop new techniques for video denoising. Spatial video denoising using wavelet transform has been the focus of the current researches as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered...
We propose a new family of nonredundant 3D directional transforms that are useful for video signals. In our construction, taking into account the correlation amongst frames of video, we first decorrelate the temporal data using a stage of 1D wavelet transform and then we employ the efficient 2D Hybrid Wavelets and Directional filter banks (HWD) transform family to the resulting spatial data where...
The Performance of various estimators, such as minimum mean square error (MMSE) is strongly dependent on correctness of the proposed model for original data distribution. Therefore, the selection of a proper model for distribution of wavelet coefficients is important in wavelet based image denoising. This paper presents a new image denoising algorithm based on the modeling of wavelet coefficients...
This paper presents image denoising methods performed within wavelet domain scheme by using wavelet packet zerotrees, and at the same time incorporating neighbor and inter-subband dependencies through NeighShrink and BiShrink [1] shrinkage functions, respectively. In particular, we call our proposed method as adaptive wavelet bivariate maximum a posteriori estimator (MAP) with NeighShrink threshold...
A new image denoising algorithm based on contourlet transform is presented in this paper. The new approach takes the correlations of inter-scale contourlet coefficients into account in the process of shrinkage, and assumes that the noise-free contourlet coefficients are correlated to their parent coefficients which locate at a different scale. By computing the relativity coefficients across scales,...
In this paper, we put forward an improved image denoising method based on multi-wavelet transform. According to the characteristic of the multi-wavelet coefficients in different directions of the different sub-band and combine with the image decomposition scaling function, this method can select different adaptive threshold of the best. Experiments show that this method can remove the white noise...
In this paper, a new shrink theory and denoising algorithm for image with Gaussian noise based on complex wavelet transform is presented and investigated. We calculate threshold value by a moving window, we can obtain different threshold values for different coefficients using our method. We modify the noisy wavelet coefficients using bivariate shrinkage method, the shrinkage functions do not assume...
This paper introduces a recently designed dual-tree complex wavelet and studies its application in image denoising. The primal filter bank is selected to be the Daubechies 9/7 filter bank, and the dual filter bank is designed to have length of 10/8; both filter banks are biorthogonal and symmetric. The wavelets of the dual-tree filter bank form (almost) Hilbert transform pairs, allowing nearly shift-invariance...
This paper presents a new video denoising algorithm based on the modeling of wavelet coefficients in each subband with a bivariate Cauchy probability density function (pdf). This bivariate pdf takes into account the statistical dependency of wavelet coefficients in adjacent scales. Within this framework, we describe a novel method for video denoising based on designing a maximum a posteriori (MAP)...
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