A proficient method for periodic and quasi-periodic noise fading using spectral histogram thresholding with sinc restoration filter

Chakraborty, Debolina; Tarafder, Milan Kumar; Chakraborty, Anirban; Banerjee, Ayan

doi:10.1016/j.aeue.2016.09.003

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…To mitigate the aforesaid problem, one fully adaptive filtration framework is proposed here, named as ‘ASRF’. As a first step, a ‘sinc filtering profile (SFP)’ [35] is considered which can automatically fit well within a specific

W^{normalF} * W^{normalF}

unlike WGNF and AGNF. As ‘noise spectrum profile ( N P )’ can be of any shape, there may be unwanted filtering due to the mismatch between the shapes of SFP and N P within a specific

W^{normalF} * W^{normalF}

.…”

Section: Proposed Asrf Methodsmentioning

confidence: 99%

Automated spectral domain approach of quasi‐periodic denoising in natural images using notch filtration with exact noise profile

Chakraborty

Banerjee

et al. 2018

IET image process

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The domain of noise fading from digital images, by virtue of its enormous appellation amongst the researchers, stands out uniquely in the recent research field of image processing over the last few decades. Periodic noises are unintended spurious signals which often agitate an image during acquisition/transmission, thereby resulting in repetitive patterns having spatial dependency and extensively demeaning visual excellence of the image. However, high amplitude noisy spectral components are clearly noticeable from the remaining uncorrupted ones in the corresponding Fourier transformed corrupted image spectrum. Hence, it is easier to distinguish and minimise those noisy components using an appropriate thresholding and filtration technique. Therefore, to start with, a simple yet elegant model of the noise-free natural image has been developed from the corrupted one followed by a proper thresholding method to get the noisy bitmap. Finally, an elegant adaptive sinc restoration filter with the concept of extracting the exact shape of a noise spectrum profile has been applied in the filtration phase. The performance of the proposed algorithm has been assessed both visually and statistically with other state-of-the-art algorithms in the literature in terms of various performance measurement attributes, providing evidence of achieving more effective restoration with considerable lower computational time.

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W^{normalF} * W^{normalF}

unlike WGNF and AGNF. As ‘noise spectrum profile ( N P )’ can be of any shape, there may be unwanted filtering due to the mismatch between the shapes of SFP and N P within a specific

W^{normalF} * W^{normalF}

.…”

Section: Proposed Asrf Methodsmentioning

confidence: 99%

Automated spectral domain approach of quasi‐periodic denoising in natural images using notch filtration with exact noise profile

Chakraborty

Banerjee

et al. 2018

IET image process

Self Cite

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show abstract

“…However, these algorithms make misclassifications in noise detection when applied on noisy peak areas corresponding to strong periodic noise that fall in the LFRs of the Fourier transformed image. Chakraborty et al filter [28] used frequency domain histogram based thresholding operation for identifying noisy areas, but this method produces misclassifications in noise detection when the noise strength is high. The noisy peak detection procedures employed by Sur et al filter [29], windowed adaptive switching minimum filter (WASMF) [30], Laplacian‐based frequency domain filter (LFDF) [31], Chakraborty filter [32], Ketenci filter [33] and Ionita filter [34] use static approximation functions but are not adaptive to the noise and image types.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Gaussian notch filter for removing periodic noise from digital images

Varghese

Subhash

Subramaniam

et al. 2020

IET Image Processing

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“…Till date, many algorithms have been proposed to alleviate noisy effect while preserving the authentic image information and thereby improving the image quality in frequency domain which has proved to be much better solution than the spatial domain operations. Giuseppe Palma et al [2] depicted that Non-Local Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many research fields. High computational complexity led to implementations on Graphic Processor Unit (GPU) architectures, which achieve reasonable running times by filtering, slice-by-slice, 3D datasets with a 2D NLM approach.…”

Section: Filtermentioning

confidence: 99%

“…For example, the image excellence can get degraded by introducing periodic unwanted pattern generated from electrical interference from an electro-mechanical device, image receiver systems and the receiving signal with the presence of another independent periodic signal etc. Many modern digital cameras having CCD or CMOS sensors [2] contain various types of electronic circuitry operating with microvolt level signals like CCD, CCD pre-amplifier, CDS signal processor and ADC. These are very susceptible to any kind of electronic interference.…”

Section: Tiff (Tagged Image File Format)mentioning

confidence: 99%

Image Filtering Techniques and Its Applications: A Review

Kaur¹,

Aggarwal²

2017

IJARCSSE

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Abstract-Noise is always presents in digital images during image acquisition, coding, transmission, and processing steps. Noise is very difficult to remove it from the digital images without the prior knowledge of noise model. That is why, review of noise models are essential in the study of image denoising techniques. In this paper, we express a brief overview of various noise models. These noise models can be selected by analysis of their origin. In this way, we present a complete and quantitative analysis of noise models available in digital images.

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A proficient method for periodic and quasi-periodic noise fading using spectral histogram thresholding with sinc restoration filter

Cited by 11 publications

References 7 publications

Automated spectral domain approach of quasi‐periodic denoising in natural images using notch filtration with exact noise profile

Automated spectral domain approach of quasi‐periodic denoising in natural images using notch filtration with exact noise profile

Adaptive Gaussian notch filter for removing periodic noise from digital images

Image Filtering Techniques and Its Applications: A Review

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