Document Detail


Optimum sensors for color constancy in scenes illuminated by daylight.
MedLine Citation:
PMID:  20922010     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
The apparent color of an object within a scene depends on the spectrum of the light illuminating the object. However, recording an object's color independent of the illuminant spectrum is important in many machine vision applications. In this paper the performance of a blackbody-model-based color constancy algorithm that requires four sensors with different spectral responses is investigated under daylight illumination. In this investigation sensor noise was modeled as gaussian noise, and the responses were quantized using different numbers of bits. A projection-based algorithm whose output is invariant to illuminant is investigated to improve the results that are obtained. The performance of both of these algorithms is then improved by optimizing the spectral sensitivities of the four sensors using freely available CIE standard daylight spectra and a set of lightness-normalized Munsell reflectance data. With the optimized sensors the performance of both algorithms is shown to be comparable to the human visual system. However, results obtained with measured daylight spectra show that the standard daylights may not be sufficiently representative of measured daylight for optimization with the standard daylight to lead to a reliable set of optimum sensor characteristics.
Authors:
Sivalogeswaran Ratnasingam; Steve Collins; Javier Hernández-Andrés
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of the Optical Society of America. A, Optics, image science, and vision     Volume:  27     ISSN:  1520-8532     ISO Abbreviation:  J Opt Soc Am A Opt Image Sci Vis     Publication Date:  2010 Oct 
Date Detail:
Created Date:  2010-10-05     Completed Date:  2011-01-28     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9800943     Medline TA:  J Opt Soc Am A Opt Image Sci Vis     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2198-207     Citation Subset:  -    
Affiliation:
Institute of Image Communication and Information Processing, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. wmeng@sjtu.edu.cn
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