Switching degenerate diffusion PDE filter based on impulselike probability for universal impulse noise removal

Chen, Xia; Tang, Chen; Yan, Xiusheng

doi:10.1016/j.aeue.2014.03.012

Cited by 3 publications

(22 citation statements)

References 26 publications

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“…Equation 8describes a spatio-temporal spreading of the number density I(x, y, t) in which the current value of the number density is updated by a statistical estimate of flux density which tends to reach an equilibrium state such that I(x, y, p + 1) = I(x, y, p) after some t = p + 1 when the probability density distribution of the process settles to Gaussian [16]. Equations (4)- (8) are based on the continuum hypothesis; for sampled time and space variables, the last equation becomes…”

Section: A First-order Robust Diffusion Smoothing Model Based On Einsmentioning

confidence: 99%

“…This is in contrast to the well-established mean filter [19], PDE-based diffusion smoothing filters [20], bilateral filters [21], and guided filters [22,23] which are not intrinsically robust. They require pre-diffusion processing and elaborate post-diffusion processing for good performance in the presence of outliers [4][5][6][7][8][9][10][19][20][21][22][23]. It is shown in Section 3 that (14) provides smoothing, Gaussian and impulse noise elimination, and edge preservation and is intrinsically robust.…”

Section: A First-order Robust Diffusion Smoothing Model Based On Einsmentioning

confidence: 99%

“…Ham et al [5] introduced an adaptive robust scale-space filter in which the robustness is provided by the incorporation of a normalization term. Subsequent developments [6][7][8][9][10][11][12][13] have followed these foundational models [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…The filter selects the mode in accordance with a local difference factor of the pixel. Xia et al [8] proposed a two-stage diffusion filter, which employs a switching function in the diffusion algorithm. The filter is designed to handle both salt and pepper noise-corrupted and random-valued impulse noise-corrupted images.…”

Section: Introductionmentioning

confidence: 99%

“…Existing robust diffusion smoothing filters [4][5][6][7][8][9][10][11][12][13] employ a variety of additional nonlinear techniques for improving the performance in the presence of outliers. They are generally complex in terms of hardware (adders and multipliers) and are not power efficient.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A robust anisotropic diffusion filter with low arithmetic complexity for images

Nair¹,

Ebenezer

Rajagopal³

2019

J Image Video Proc.

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Image smoothing with edge preservation in the presence of outliers is a challenge in image processing. Anisotropic diffusion smoothing is a well-established paradigm in digital image smoothing with edge preservation. Anisotropic diffusion smoothing filters are not robust to impulse noise. They employ two or more stages for robustness in the presence of outliers, and, therefore, they demand significantly increased arithmetic operations for robustness; consequently, they are not power efficient. This paper introduces a low arithmetic complexity image smoothing model and proposes an intrinsically robust and power efficient algorithm for anisotropic diffusion smoothing of images. The algorithm outperforms the foundational robust smoothing algorithms in terms of the standard performance metrics and visual quality.

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Section: A First-order Robust Diffusion Smoothing Model Based On Einsmentioning

confidence: 99%

Section: A First-order Robust Diffusion Smoothing Model Based On Einsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A robust anisotropic diffusion filter with low arithmetic complexity for images

Nair¹,

Ebenezer

Rajagopal³

2019

J Image Video Proc.

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Impulsive adaptive observer design for a class of hybrid ODE–PDE cascade systems with uncertain parameters

Wen

Lou

et al. 2021

Systems & Control Letters

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Study and Implementation of Various Image De-Noising Methods for Traffic Sign Board Recognition

Subashini¹,

Deshpande²,

Ramani³

2019

Adv. sci. technol. eng. syst. j.

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The problem of recognizing traffic sign boards in a correct fashion is one of the major challenges since there is an alarming rate of increase in the number of road accidents happening because of incorrect interpretation of traffic sign boards in bad weather conditions. In this paper, a comparative analysis of various noise removal techniques based on calculating different parameters which decide the quality of input roadway symbol like Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) as well as Structural Similarity for measuring Image Quality (SSIM) is being performed and the best technique will be chosen among them which gives minimum Mean Squared Error (MSE) value and maximum Peak Signal to Noise Ratio (PSNR) and Structural Similarity for measuring the Image Quality (SSIM) values. This technique will be quite useful for de-noising a given image which is present in both the testing and the training image databases.

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Switching degenerate diffusion PDE filter based on impulselike probability for universal impulse noise removal

Cited by 3 publications

References 26 publications

A robust anisotropic diffusion filter with low arithmetic complexity for images

A robust anisotropic diffusion filter with low arithmetic complexity for images

Impulsive adaptive observer design for a class of hybrid ODE–PDE cascade systems with uncertain parameters

Study and Implementation of Various Image De-Noising Methods for Traffic Sign Board Recognition

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