A contrast enhancement framework under uncontrolled environments based on just noticeable difference

↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Search: WFRF:(Tan Kai) > (2020-2024) > A contrast enhancem...

Details
MARC

Hum, Yan ChaiDepartment of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia (author)

A contrast enhancement framework under uncontrolled environments based on just noticeable difference

Article/chapterEnglish2022

Publisher, publication year, extent ...

Elsevier,2022
printrdacarrier

Numbers

LIBRIS-ID:oai:DiVA.org:ltu-89816
https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-89816URI
https://doi.org/10.1016/j.image.2022.116657DOI

Supplementary language notes

Language:English
Summary in:English

Part of subdatabase

SwePubSwePub

Classification

Subject category:ref swepub-contenttype
Subject category:art swepub-publicationtype

Notes

Validerad;2022;Nivå 2;2022-03-21 (johcin);Funder: UTAR Research Fund (IPSR/RMC/UTARRF/2020-C1/H02).
Image contrast enhancement refers to an operation of remapping the pixels’ values of an image to emphasize desired information in the image. In this work, we propose a novel pixel-based (local) contrast enhancement algorithm, based on the human visual perception. First, we make an observation that pixels with lower regional contrast should be amplified for the purpose of enhancing the contrast and pixels with higher regional contrast should be suppressed to avoid undesired over-enhancement. To determine the quality of the regional contrast in the image (either lower or higher), a reference image will be created using a proposed global based contrast enhancement method (termed as Mean Brightness Bidirectional Histogram Equalization in the paper) for fast computation reason. To quantify the abovementioned regional contrast, we propose a method based on human visual perception taking Just Noticeable Difference (JND) into account. In short, our proposed algorithm is able to limit the enhancement of well-contrasted regions and enhance the poor contrast regions in an image. Both objective quality and subjective quality experimental results suggested that the proposed algorithm enhances images consistently across images with different dynamic range. We conclude that the proposed algorithm exhibits excellent consistency in producing satisfactory result for different type of images. It is important to note that the algorithm can be directly implemented in color space and not limited only to grayscale. The proposed algorithm can be obtained from the following GitHub link: https://github.com/UTARSL1/CHE.

Subject headings and genre

NATURVETENSKAP Data- och informationsvetenskap Datavetenskap hsv//swe
NATURAL SCIENCES Computer and Information Sciences Computer Sciences hsv//eng
Contrast enhancement
Image enhancement
Histogram equalization
Machine Learning
Maskininlärning

Added entries (persons, corporate bodies, meetings, titles ...)

Tee, Yee KaiDepartment of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia (author)
Yap, Wun-SheDepartment of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia (author)
Mokayed, HamamLuleå tekniska universitet,EISLAB(Swepub:ltu)mokham (author)
Tan, Tian SweeBioInspired Device and Tissue Engineering Research Group, School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia (author)
Salim, Maheza Irna MohamadDiagnostic Research Group, School of Biomedical Engineering and Health Sciences, School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia (author)
Lai, Khin WeeDepartment of Biomedical Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia (author)
Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, MalaysiaDepartment of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia (creator_code:org_t)

Related titles

In:Signal processing. Image communication: Elsevier1030923-59651879-2677

Internet link

Find in a library

Signal processing. Image communication (Search for host publication in LIBRIS)

To the university's database

Find more in SwePub

By the author/editor: Hum, Yan Chai; Tee, Yee Kai; Yap, Wun-She; Mokayed, Hamam; Tan, Tian Swee; Salim, Maheza Ir ...; show more...; Lai, Khin Wee; show less...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

Articles in the publication: Signal processin ...

By the university: Luleå University of Technology

Search outside SwePub

Extend your search to:: Google; Google Book Search; Google Scholar

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se