Object
Title: Combination of Single Image Super Resolutionand Digital Inpainting Algorithms Based onGANs for Robust Image Completion
Co-author(s) :
Karapetyan Gevorg ; Voronin Viacheslav ; Sarukhanyan Hakob
Abstract:
Image inpainting, a technique of completing missing or corrupted image regions in undetected form, is an open problem in digital image processing. Inpainting of large regions using Deep Convolutional Generative Adversarial Nets (DCGAN) is a new and powerful approach. In described approaches the size of generated image and size of input image should be the same. In this paper we propose a new method where the size of input image with corrupted region can be up to 4 times larger than generated image.
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Date created:
Identifier:
oai:noad.sci.am:135825
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Journal or Publication Title:
Serbian journal of electrical engineering
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Additional Information:
sparik_hayrapetyan@edu.aua.am ; gevorgk@ipia.sci.am; hakop@ipia.sci.am
Affiliation:
American University of Armenia ; Institute for Informatics and Automation Problems ; Don State Technical University
Country:
Indexing:
Object collections:
- Digital Library > Academic Insitutions > Insitute for Informatics and Automation Problems of NAS RA > Publications
Last modified:
Mar 3, 2021
In our library since:
Jul 20, 2020
Number of object content hits:
10
All available object's versions:
https://noad.sci.am/publication/149358
