Edge-Preserving Image Denoising Based on Lipschitz Estimation

Autor: Zunera Jalil, Bushra Jalil, Eric Fauvet, Olivier Laligant
Přispěvatelé: Equipe VIBOT - VIsion pour la roBOTique [ImViA EA7535 - ERL CNRS 6000] (VIBOT), Centre National de la Recherche Scientifique (CNRS)-Imagerie et Vision Artificielle [Dijon] (ImViA), Université de Bourgogne (UB)-Université de Bourgogne (UB)
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Jalil
Technology
Computer science
QH301-705.5
Noise reduction
QC1-999
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Signal
Edge detection
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
E
0202 electrical engineering
electronic engineering
information engineering
denoising
Z
General Materials Science
Biology (General)
Instrumentation
QD1-999
ComputingMilieux_MISCELLANEOUS
Continuous wavelet transform
Fluid Flow and Transfer Processes
edge detection
Lipschitz estimation
Noise (signal processing)
Process Chemistry and Technology
Physics
General Engineering
020206 networking & telecommunications
Fauvet
Lipschitz continuity
Engineering (General). Civil engineering (General)
Computer Science Applications
B
Laligant
Discontinuity (linguistics)
Chemistry
020201 artificial intelligence & image processing
TA1-2040
Maxima
O. Edge-Preserving Image Denoising Based on Lipschitz denoising
Algorithm
Zdroj: Applied Sciences, Vol 11, Iss 5126, p 5126 (2021)
Applied Sciences
Applied Sciences, MDPI, 2021, 11, ⟨10.3390/app11115126⟩
Volume 11
Issue 11
ISSN: 2076-3417
DOI: 10.3390/app11115126⟩
Popis: 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.
Databáze: OpenAIRE
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