Edge-Preserving Image Denoising Based on Lipschitz Estimation Article Swipe
Bushra Jalil
,
Zunera Jalil
,
Éric Fauvet
,
Olivier Laligant
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/app11115126
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/app11115126
The information transmitted in the form of signals or images is often corrupted with noise. These noise elements can occur due to the relative motion, noisy channels, error in measurements, and environmental conditions (rain, fog, change in illumination, etc.) and result in the degradation of images acquired by a camera. In this paper, we address these issues, focusing mainly on the edges that correspond to the abrupt changes in the signal or images. Preserving these important structures, such as edges or transitions and textures, has significant theoretical importance. These image structures are important, more specifically, for visual perception. The most significant information about the structure of the image or type of the signal is often hidden inside these transitions. Therefore it is necessary to preserve them. This paper introduces a method to reduce noise and to preserve edges while performing Non-Destructive Testing (NDT). The method computes Lipschitz exponents of transitions to identify the level of discontinuity. Continuous wavelet transform-based multi-scale analysis highlights the modulus maxima of the respective transitions. Lipschitz values estimated from these maxima are used as a measure to preserve edges in the presence of noise. Experimental results show that the noisy data sample and smoothness-based heuristic approach in the spatial domain restored noise-free images while preserving edges.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app11115126
- https://www.mdpi.com/2076-3417/11/11/5126/pdf?version=1622771911
- OA Status
- gold
- Cited By
- 1
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3171857783
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3171857783Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app11115126Digital Object Identifier
- Title
-
Edge-Preserving Image Denoising Based on Lipschitz EstimationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-05-31Full publication date if available
- Authors
-
Bushra Jalil, Zunera Jalil, Éric Fauvet, Olivier LaligantList of authors in order
- Landing page
-
https://doi.org/10.3390/app11115126Publisher landing page
- PDF URL
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https://www.mdpi.com/2076-3417/11/11/5126/pdf?version=1622771911Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2076-3417/11/11/5126/pdf?version=1622771911Direct OA link when available
- Concepts
-
Noise (video), Artificial intelligence, Lipschitz continuity, Wavelet, Computer science, Computer vision, Noise reduction, Discontinuity (linguistics), Mathematics, Robustness (evolution), Pattern recognition (psychology), Algorithm, Image (mathematics), Mathematical analysis, Biochemistry, Gene, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
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31Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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