Pixel similarity-based adaptive Riesz mean filter for salt-and-pepper noise removal

Enginoğlu, Serdar; Erkan, Uğur; Memiş, Samet

doi:10.1007/s11042-019-08110-1

Cited by 55 publications

(30 citation statements)

References 29 publications

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“…The Adaptive Riesz Mean Filter (ARMF [25]) initially creates a binary bitmap based on whether a given pixel is noisy or non-noisy, it assigns it a value of 0 or 1 respectively. It takes into consideration a window of variable size, the size of which is determined by values in its corresponding bitmap.…”

Section: Related Workmentioning

confidence: 99%

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A novel hybrid decision-based filter and universal edge-based logical smoothing add-on to remove impulsive noise

Ghumaan¹,

Sohi²,

Sharma³

et al. 2021

Turk J Elec Eng & Comp Sci

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This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at very high noise density. The proposed filter initially specifies a threshold and then de-noises the image using combination of linear, non-linear and probabilistic techniques. Further, to improve quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that proposed filter is able to restore image details even at extremely high noise density of 99%. Further, the proposed filter provides admirable results on natural as well as medical images from very low to very high noise density. Finally, it is observed that the proposed filter on an average improves the PSNR by 11% over the state-of-the-art technique.

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Section: Related Workmentioning

confidence: 99%

“…The simulation is performed for the proposed and other state-of-the-art filters namely ArMF [25], MDBUTMF, FSBMMF, RSIF, TVWA, ASWMF and DAMF. Different benchmark images are considered for analysis.…”

Section: Simulationmentioning

confidence: 99%

A novel hybrid decision-based filter and universal edge-based logical smoothing add-on to remove impulsive noise

Ghumaan¹,

Sohi²,

Sharma³

et al. 2021

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…Enginoğlu et al. [23] propose a adaptive Riesz mean filter (ARmF), by operationalizing pixel similarity for salt and pepper noise removal. Erkan et al.…”

Section: Introductionmentioning

confidence: 99%

An image denoising algorithm based on adaptive clustering and singular value decomposition

Wang

et al. 2021

IET Image Processing

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Self‐similarity, a prior of natural images, has attracted much attention. The attribute means that low‐rank group matrices can be constructed from similar image patches. For low‐rank approximation denoising methods based on singular value decomposition (SVD) the ability to accurately construct group matrices with noise and handle singular values are keys. Here, combining image priors, a two‐stage clustering method to adaptively construct group matrices is designed. The method is anti‐noise, that is, when noise levels are high, these matrices are more accurate than that constructed by other algorithms. Then, according to the significance of singular values and singular vectors, singular vectors of the low‐rank estimations are corrected so that the residual noise in the low‐rank estimations is further suppressed. For back projection , the authors use the original noise level and the residual image to adaptively determine projection parameters and new noise levels . So, authors' back projection can provide a good foundation for authors' two‐stage denoising methods, better remove noise and preserve image details. Experimental results show that compared with the existing state‐of‐the‐art denoising algorithms, the proposed algorithm achieves competitive denoising performances in terms of quantitative metrics and preserving details. Especially with the increase of noise, the competitiveness of authors' algorithms is gradually enhanced.

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“…There are many types of noise such as Gaussian noise [10], Poisson noise [11–13] and impulse noise [14–18]. Salt‐and‐pepper noise (SPN) is a simple form of impulse noise and it is common in many electronic devices.…”

Section: Introductionmentioning

confidence: 99%

Adaptive frequency median filter for the salt and pepper denoising problem

Erkan

Enginoğlu

Thanh

et al. 2020

IET Image Processing

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Pixel similarity-based adaptive Riesz mean filter for salt-and-pepper noise removal

Abstract: In this study, we propose a new method, i.e. Adaptive Riesz Mean Filter (ARmF), by operationalizing pixel similarity for salt-and-pepper noise (SPN) removal.

Cited by 55 publications

References 29 publications

A novel hybrid decision-based filter and universal edge-based logical smoothing add-on to remove impulsive noise

A novel hybrid decision-based filter and universal edge-based logical smoothing add-on to remove impulsive noise

An image denoising algorithm based on adaptive clustering and singular value decomposition

Adaptive frequency median filter for the salt and pepper denoising problem

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