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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2013 - 16

Logarithmic Type Image Processing Framework for Enhancing Photographs Acquired in Extreme Lighting

FLOREA, C. See more information about FLOREA, C. on SCOPUS See more information about FLOREA, C. on IEEExplore See more information about FLOREA, C. on Web of Science, FLOREA, L. See more information about FLOREA, L. on SCOPUS See more information about FLOREA, L. on SCOPUS See more information about FLOREA, L. on Web of Science
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Download PDF pdficon (768 KB) | Citation | Downloads: 500 | Views: 3,321

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

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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.

References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 1,552 TCR
SCOPUS® Citations for all references: 2,530 TCR

Web of Science® Average Citations per reference: 34 ACR
SCOPUS® Average Citations per reference: 56 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-11-22 18:41 in 168 seconds.

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