Sökning: WFRF:(Tan Kai) >
A contrast enhancem...
A contrast enhancement framework under uncontrolled environments based on just noticeable difference
-
- Hum, Yan Chai (författare)
- Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
-
- Tee, Yee Kai (författare)
- Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
-
- Yap, Wun-She (författare)
- Department of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
-
visa fler...
-
- Mokayed, Hamam (författare)
- Luleå tekniska universitet,EISLAB
-
- Tan, Tian Swee (författare)
- BioInspired Device and Tissue Engineering Research Group, School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
-
- Salim, Maheza Irna Mohamad (författare)
- Diagnostic 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
-
- Lai, Khin Wee (författare)
- Department of Biomedical Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
-
visa färre...
-
(creator_code:org_t)
- Elsevier, 2022
- 2022
- Engelska.
-
Ingår i: Signal processing. Image communication. - : Elsevier. - 0923-5965 .- 1879-2677. ; 103
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Contrast enhancement
- Image enhancement
- Histogram equalization
- Machine Learning
- Maskininlärning
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas