TY - JOUR
T1 - A linear system form solution to compute the local space average color
AU - Salas, Joaquin
AU - Tomasi, Carlo
N1 - Funding Information:
Thanks to Marc Ebner for providing the original images for Fig. , to Mary Masterman for editing the document, and to the reviewers whose comments improved greatly the quality of our exposition. This work was partially supported by the Fomix CONACYT-DF under Grant No. 189005 and the Instituto Politecnico Nacional under Grant No. 20131832 for Joaquin Salas, and the National Science Foundation under Grant No. IIS-1017017 and by the Army Research Office under Grant No. W911NF-10-1-0387 for Carlo Tomasi.
PY - 2013/10
Y1 - 2013/10
N2 - In this document, we present an alternative to the method introduced by Ebner (Pattern Recognit 60-67, 2003; J Parallel Distrib Comput 64(1):79-88, 2004; Color constancy using local color shifts, pp 276-287, 2004; Color Constancy, 2007; Mach Vis Appl 20(5):283-301, 2009) for computing the local space average color. We show that when the problem is framed as a linear system and the resulting series is solved, there is a solution based on LU decomposition that reduces the computing time by at least an order of magnitude.
AB - In this document, we present an alternative to the method introduced by Ebner (Pattern Recognit 60-67, 2003; J Parallel Distrib Comput 64(1):79-88, 2004; Color constancy using local color shifts, pp 276-287, 2004; Color Constancy, 2007; Mach Vis Appl 20(5):283-301, 2009) for computing the local space average color. We show that when the problem is framed as a linear system and the resulting series is solved, there is a solution based on LU decomposition that reduces the computing time by at least an order of magnitude.
KW - Color constancy
KW - Gray-world assumption
KW - Local space average color
UR - http://www.scopus.com/inward/record.url?scp=84885303341&partnerID=8YFLogxK
U2 - 10.1007/s00138-013-0494-0
DO - 10.1007/s00138-013-0494-0
M3 - Artículo
SN - 0932-8092
VL - 24
SP - 1555
EP - 1560
JO - Machine Vision and Applications
JF - Machine Vision and Applications
IS - 7
ER -