loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Author: Selcuk Ilhan Aydi

Affiliation: Institute of Science, Faculty of Computer Engineering, Gebze Technical University, Turkey

Keyword(s): Image Quality Assessment, Sparse Coding, Human Visual System.

Abstract: In this paper, the image quality assessment problem is tackled from a sparse coding perspective, and a new automated image quality assessment algorithm is presented. Specifically, the input image is first divided into non-overlapping blocks and sparse coding is used to reconstruct a central sub-block using the neighboring sub-blocks as dictionaries. The resulting 2D sparse vectors from each neighboring sub-block, are devised as significance maps that are then used in similarity measures between the reference and distorted images. The proposed method is compared against various recently introduced shallow and deep methods across four datasets and multiple distortion types. The experimental results that have been obtained show that it possesses a strong correlation with the Human Visual System and outperforms its counterparts.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.22.224.16

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Aydi, S. (2022). An Image Quality Assessment Method based on Sparse Neighbor Significance. In Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE; ISBN 978-989-758-563-0; ISSN 2795-4943, SciTePress, pages 34-44. DOI: 10.5220/0011058700003209

@conference{improve22,
author={Selcuk Ilhan Aydi.},
title={An Image Quality Assessment Method based on Sparse Neighbor Significance},
booktitle={Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE},
year={2022},
pages={34-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011058700003209},
isbn={978-989-758-563-0},
issn={2795-4943},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE
TI - An Image Quality Assessment Method based on Sparse Neighbor Significance
SN - 978-989-758-563-0
IS - 2795-4943
AU - Aydi, S.
PY - 2022
SP - 34
EP - 44
DO - 10.5220/0011058700003209
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic