Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction

In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion to what happens in the theoretical Sobolev spa...

Full description

Bibliographic Details
Main Authors: Seracini, Marco, Brown, Stephen R.
Format: Article
Published: Multidisciplinary Digital Publishing Institute 2023
Online Access:https://hdl.handle.net/1721.1/152035
_version_ 1811080843468210176
author Seracini, Marco
Brown, Stephen R.
author_facet Seracini, Marco
Brown, Stephen R.
author_sort Seracini, Marco
collection MIT
description In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion to what happens in the theoretical Sobolev spaces: its use reduces the uncertainty in the choice of the most suitable values for each point to inpaint. Moreover, we introduce a probabilistic model by which we prove that the usual principal directions, generally employed for continuous problems, are not enough to achieve consistent reconstructions in the discrete inpainting asset. Finally, we formalize a new priority index and new rules for its dynamic update. The quality of the reconstructions, achieved using a reduced neighborhood size of more than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>95</mn><mo>%</mo></mrow></semantics></math></inline-formula> with respect to the current state-of-the-art algorithms based on the same inpainting approach, further provides the experimental validation of the method.
first_indexed 2024-09-23T11:37:45Z
format Article
id mit-1721.1/152035
institution Massachusetts Institute of Technology
last_indexed 2024-09-23T11:37:45Z
publishDate 2023
publisher Multidisciplinary Digital Publishing Institute
record_format dspace
spelling mit-1721.1/1520352023-09-07T03:31:50Z Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction Seracini, Marco Brown, Stephen R. In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion to what happens in the theoretical Sobolev spaces: its use reduces the uncertainty in the choice of the most suitable values for each point to inpaint. Moreover, we introduce a probabilistic model by which we prove that the usual principal directions, generally employed for continuous problems, are not enough to achieve consistent reconstructions in the discrete inpainting asset. Finally, we formalize a new priority index and new rules for its dynamic update. The quality of the reconstructions, achieved using a reduced neighborhood size of more than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>95</mn><mo>%</mo></mrow></semantics></math></inline-formula> with respect to the current state-of-the-art algorithms based on the same inpainting approach, further provides the experimental validation of the method. 2023-09-06T19:23:00Z 2023-09-06T19:23:00Z 2023-08-18 2023-08-25T12:37:10Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/152035 Applied Sciences 13 (16): 9405 (2023) PUBLISHER_CC http://dx.doi.org/10.3390/app13169405 Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Multidisciplinary Digital Publishing Institute Multidisciplinary Digital Publishing Institute
spellingShingle Seracini, Marco
Brown, Stephen R.
Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title_full Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title_fullStr Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title_full_unstemmed Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title_short Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction
title_sort inpainting in discrete sobolev spaces structural information for uncertainty reduction
url https://hdl.handle.net/1721.1/152035
work_keys_str_mv AT seracinimarco inpaintingindiscretesobolevspacesstructuralinformationforuncertaintyreduction
AT brownstephenr inpaintingindiscretesobolevspacesstructuralinformationforuncertaintyreduction