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Logarithmic Type Image Processing Framework for Enhancing Photographs Acquired in Extreme LightingFLOREA, C. , FLOREA, L. |
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Author keywords
digital cameras, image processing image enhancement, linear algebra
References keywords
image(27), processing(24), logarithmic(13), florea(9), vision(7), model(7), enhancement(7), systems(5), signal(5), range(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2013-05-31
Volume 13, Issue 2, Year 2013, On page(s): 97 - 104
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.02016
Web of Science Accession Number: 000322179400016
SCOPUS ID: 84878914251
Abstract
The Logarithmic Type Image Processing (LTIP) tools are mathematical models that were constructed for the representation and processing of gray tones images. By careful redefinition of the fundamental operations, namely addition and scalar multiplication, a set of mathematical properties are achieved. Here we propose the extension of LTIP models by a novel parameterization rule that ensures preservation of the required cone space structure. To prove the usability of the proposed extension we present an application for low-light image enhancement in images acquired with digital still camera. The closing property of the named model facilitates similarity with human visual system and digital camera processing pipeline, thus leading to superior behavior when compared with state of the art methods. |
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[1] Diverse image enhancer for complex underexposed image, Rahman, Ziaur, Ali, Zafar, Khan, Inayat, Uddin, Muhammad Irfan, Guan, Yurong, Hu, Zhihua, Journal of Electronic Imaging, ISSN 1017-9909, Issue 04, Volume 31, 2022.
Digital Object Identifier: 10.1117/1.JEI.31.4.041213 [CrossRef]
[2] An optimized design of the pointer meter image enhancement and automatic reading system in low illumination environment, Ge, Wenqi, Yu, Xiaogang, Hu, Xiangyu, Wang, Xiaotong, Measurement Science and Technology, ISSN 0957-0233, Issue 10, Volume 34, 2023.
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[3] Software tools for medical diagnosis support automatic interpretation of digital X-ray films, Vertan, Constantin, Florea, Corneliu, Florea, Laura, Sultana, Alina, 2013 E-Health and Bioengineering Conference (EHB), ISBN 978-1-4799-2373-1, 2013.
Digital Object Identifier: 10.1109/EHB.2013.6707395 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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