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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
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  2/2013 - 16

 HIGHLY CITED PAPER 

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: 966 | Views: 4,280

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
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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.


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References Weight

Web of Science® Citations for all references: 1,976 TCR
SCOPUS® Citations for all references: 3,284 TCR

Web of Science® Average Citations per reference: 44 ACR
SCOPUS® Average Citations per reference: 73 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 2024-04-20 14:37 in 138 seconds.




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