Removal of mixed-noise using order statistic filter and wavelet domain Wiener filter

Badulescu, P.; R, Zaciu

doi:10.1109/smicnd.1999.810523

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…So Gaussian filters are widely used in image filtering. In [51], the removal of mixed noise using order statistic filter and wavelet domain Wiener filter is proposed. Authors have evaluated two methods.…”

Section: Pre-or Post -Processingmentioning

confidence: 99%

Speckle Noise Reduction in Medical Ultrasound Images

Hiremath¹,

Akkasaligar²,

Badiger³

2013

Advancements and Breakthroughs in Ultrasound Imaging

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Section: Pre-or Post -Processingmentioning

confidence: 99%

Speckle Noise Reduction in Medical Ultrasound Images

Hiremath¹,

Akkasaligar²,

Badiger³

2013

Advancements and Breakthroughs in Ultrasound Imaging

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“…In a differential equation, if the unknown function to be solved only contains one argument, the equation is called ODE (ordinary differential equation); if the unknown function to be solved contains at least one argument, and there appears partial derivative of each order of multivariate function for different independent variables in the equation, the equation is called partial differential equation [11,12,13].…”

Section: A Basic Conceptionmentioning

confidence: 99%

Visual and Artistic Images Denoising Methods Based on Partial Differential Equation

Ye¹,

Li²,

Liu³

2013

JMM

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Partial differential equation has a remarkable effect on image denoising, compression and segmentation. Based on partial differential equations, the denoising experiment is carried out on those artistic images requiring high degree of visual reduction through the application of 3 image-denoising algorithm models including thermal diffusion equation, P-M diffusion equation and the TV diffusion equation. By this experience, the respective characteristics in image-denoising of these 3 methods can be analyzed so that a better way can be chosen in adapting to digitization of artistic images or in dealing with distant signal

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“…The Fourier transform is only localized in frequency, but wavelet transform are localized in both time and frequency. Fast wavelet transform(FWT) is a computationally efficient implementation of wavelet transform [2][3][4] . If scaling vector is h, and wavelet vector is g, scaling and wavelet functions can be derived：…”

Section: The Theory Of Wavelet Transformmentioning

confidence: 99%

“…The other is based on image restoration method, this method doesn't need to establish the atmospheric model and directly enhance fog-degraded image details ] .Some previous image restoration algorithms only consider noise reduction and do not care about detail restoration. Some image restoration algorithms are reversed [1][2][3][4][5][6][7][8] . This paper presents a new wavelet-based method that considers both detail restoration and noise reduction.…”

Section: Introductionmentioning

confidence: 99%

A Novel Image Contrast Restoration Algorithm for Fog

Zhao

2013

AMR

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Images captured in fog suffer from low contrast, restoration of fog- degraded images are needed. In this paper, a novel algorithm of image restoration based on wavelet semi-soft threshold is presented. The results show detail restoration and de-noising are improved effectively comparing with Histogram equalization and homomorphic filtering method. It can be concluded that the new algorithm enhanced the contrast of fog-degraded image well.

show abstract

Removal of mixed-noise using order statistic filter and wavelet domain Wiener filter

Cited by 8 publications

References 7 publications

Speckle Noise Reduction in Medical Ultrasound Images

Speckle Noise Reduction in Medical Ultrasound Images

Visual and Artistic Images Denoising Methods Based on Partial Differential Equation

A Novel Image Contrast Restoration Algorithm for Fog

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