Image denoising method based on non-uniform partition and wavelet transform

Song, Ruixia; Li, Yanan; Zhang, Qiaoxia; Zhao, Zhaoxia

doi:10.1109/cisp.2010.5647188

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Hence, image denoising [1][2][3][4] becomes a necessary preprocessing step in some cases. Various image filtering methods have been utilized to perform denoising operation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Median Filter Based on SNR Estimation of Single Image

Zhang²,

Lin³

2012

2012 International Conference on Computer Science and Service System

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An adaptive median filtering method based on SNR estimation of single image is presented in this paper. The proposed method first innovatively estimates SNR of an image degraded by salt & pepper noise, and then adaptively chooses window size of median filter. Estimation of single image's SNR provides guidance for the judgment on noisy or non-noisy image, and even noise density. This is helpful for dealing with salt & pepper noise, such as adaptive determination of window size in median filter. The new method was compared with classic median filter with fixed window size on a variety of images, and experimental results show its effectiveness.

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“…Hence, image denoising [1][2][3][4] becomes a necessary preprocessing step in some cases. Various image filtering methods have been utilized to perform denoising operation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Median Filter Based on SNR Estimation of Single Image

Zhang²,

Lin³

2012

2012 International Conference on Computer Science and Service System

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“…Among several denoising algorithms, denoising that based on wavelet transform for cancelling white Gaussian noise finds wide range of applications since the pioneer work by Donoho and Johnstone [1]. VisuShrink [1], SureShrink [2], BayesShrink [3], SURE-LET [4], NUP/Wavelet transform [5], and Neural Network based thresholding [6] are examples of thresholding the wavelet detail coefficients term by term based on their individual magnitudes. Thereafter, several alternative denoising algorithms have been proposed by many authors that based on utilizing the information about the neighbor wavelet coefficients (block of coefficients) rather than individually.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Implementation of Neighborhood based Wavelet Thresholding For Image Denoising

Hussain¹,

Gorashi²

2012

IJCA

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In this paper we propose computationally efficient denoising algorithm that thresholds the wavelet coefficient considering its neighbors in deciding whether it is noisy or noise free. The proposed algorithm select a suboptimal threshold and neighboring window size for every subband that minimized Mean Square Error(MSE) in the denoised image using Stein's Unbiased Risk Estimate(SURE). In this paper, we demonstrate the efficiency of the proposed denoising algorithm as compared with two other state-of-the art denoising algorithms.

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Nonuniform mesh generation for images via moving mesh equation

Xie

2011

2011 4th International Congress on Image and Signal Processing

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Image denoising method based on non-uniform partition and wavelet transform

Cited by 5 publications

References 13 publications

Adaptive Median Filter Based on SNR Estimation of Single Image

Adaptive Median Filter Based on SNR Estimation of Single Image

An Efficient Implementation of Neighborhood based Wavelet Thresholding For Image Denoising

Nonuniform mesh generation for images via moving mesh equation

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