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.

Publisher:

National Library of Serbia

Date created:

2017

Identifier:

oai:noad.sci.am:135825

DOI:

10.2298/SJEE1703379H

ISSN:

1451-4869

Other identifier:

UDC: 004.932.4+004.934.72

Language:

English

Journal or Publication Title:

Serbian journal of electrical engineering

Volume:

14

Number:

3

URL:


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:

Armenia

Indexing:

Scopus

Object collections:

Last modified:

Mar 3, 2021

In our library since:

Jul 20, 2020

Number of object content hits:

4

All available object's versions:

https://noad.sci.am/publication/149358

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