Inverse Problems in Image Restoration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00638576" target="_blank" >RIV/67985556:_____/25:00638576 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/book/10.1007/978-3-031-87213-6" target="_blank" >https://link.springer.com/book/10.1007/978-3-031-87213-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-87213-6_14" target="_blank" >10.1007/978-3-031-87213-6_14</a>
Alternative languages
Result language
angličtina
Original language name
Inverse Problems in Image Restoration
Original language description
This work addresses inverse problems in image restoration, focusing on recovering high-quality images from degraded observations, a critical task in fields like microscopy and digital photography. We examine both traditional variational methods and modern deep learning techniques, highlighting hybrid approaches that merge mathematical modeling with data-driven learning. Classical model-based methods use explicit regularization, like total variation, to incorporate prior knowledge and stabilize the inversion process. Meanwhile, deep learning approaches, both supervised and self-supervised, leverage implicit regularization, where network architectures capture and learn prior information from data. We present our recent advancements in this field and discuss the effectiveness of these complementary approaches in solving complex image restoration problems in theory and practice.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA21-03921S" target="_blank" >GA21-03921S: Inverse problems in image processing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Inverse Problems: Modelling and Simulation : Extended Abstracts of the IPMS Conference 2024
ISBN
978-3-031-87212-9
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
107-113
Publisher name
Springer
Place of publication
Cham
Event location
Paradise Bay Resort Hotel
Event date
May 26, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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