A Bound Constrained Regularization for Total Variation-Based Image Denoising
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@Article{JICS-3-097,
author = {},
title = {A Bound Constrained Regularization for Total Variation-Based Image Denoising},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {3},
number = {2},
pages = {097--103},
abstract = { In this study, we use a recursive method based upon power series to solve nonlinear Volterra
integral equations system of the second kind. This method gives an approximate solution as the Taylor
expansion for the solution of the system via some simple computations. Numerical examples illustrate the
pertinent features of the method.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22772.html}
}
TY - JOUR
T1 - A Bound Constrained Regularization for Total Variation-Based Image Denoising
AU -
JO - Journal of Information and Computing Science
VL - 2
SP - 097
EP - 103
PY - 2024
DA - 2024/01
SN - 3
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22772.html
KW - Nonlinear integral equations system, Numerical method, Taylor expansion.
AB - In this study, we use a recursive method based upon power series to solve nonlinear Volterra
integral equations system of the second kind. This method gives an approximate solution as the Taylor
expansion for the solution of the system via some simple computations. Numerical examples illustrate the
pertinent features of the method.
. (2024). A Bound Constrained Regularization for Total Variation-Based Image Denoising.
Journal of Information and Computing Science. 3 (2).
097-103.
doi:
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