Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00312018" target="_blank" >RIV/68407700:21230/17:00312018 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/TIP.2017.2651374" target="_blank" >https://doi.org/10.1109/TIP.2017.2651374</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TIP.2017.2651374" target="_blank" >10.1109/TIP.2017.2651374</a>

Result language

angličtina

Original language name

Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics

Original language description

Most of the effort in image quality assessment (QA) has been so far dedicated to the degradation of the image. However, there are also many algorithms in the image processing chain that can enhance the quality of an input image. These include procedures for contrast enhancement, deblurring, sharpening, up-sampling, denoising, transfer function compensation, and so on. In this paper, possible strategies for the QA of sharpened images are investigated. This task is not trivial, because the sharpening techniques can increase the perceived quality, as well as introduce artifacts leading to the quality drop (over-sharpening). Here, the framework specifically adapted for the QA of sharpened images and objective metrics comparison in this context is introduced. However, the framework can be adopted in other QA areas as well. The problem of selecting the correct procedure for subjective evaluation was addressed and a subjective test on blurred, sharpened, and over-sharpened images was performed in order to demonstrate the use of the framework. The obtained ground-truth data were used for testing the suitability of the state-of-the-art objective quality metrics for the assessment of sharpened images. The comparison was performed by novel procedure using rank order correlation analyses, which is found more appropriate for the task than standard methods. Furthermore, seven possible augmentations of the no-reference S3 metric adapted for sharpened images are proposed. The performance of the metric is significantly improved and also superior over the rest of the tested quality criteria with respect to the subjective data.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Transactions on Image Processing

ISSN

1057-7149

e-ISSN

1941-0042

Volume of the periodical

26

Issue of the periodical within the volume

3

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

1496-1508

UT code for WoS article

000402384400001

EID of the result in the Scopus database

2-s2.0-85018464093