title: Perceptual color characterization of cameras.
abstract: Color camera characterization, mapping outputs from the camera sensors to an independent color space, such as XYZ, is an important step in the camera processing pipeline. Until now, this procedure has been primarily solved by using a 3 × 3 matrix obtained via a least-squares optimization. In this paper, we propose to use the spherical sampling method, recently published by Finlayson et al., to perform a perceptual color characterization. In particular, we search for the 3 × 3 matrix that minimizes three different perceptual errors, one pixel based and two spatially based. For the pixel-based case, we minimize the CIE ΔE error, while for the spatial-based case, we minimize both the S-CIELAB error and the CID error measure. Our results demonstrate an improvement of approximately 3% for the ΔE error, 7% for the S-CIELAB error and 13% for the CID error measures.
authors.affiliation: Information and Communications Technologies Department, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain. marcelo.bertalmio@upf.edu.
authors.forename: Javier
authors.initials: J
authors.lastname: Vazquez-Corral
authors.affiliation: Centre for Visual Computing, University of Bradford, Bradford BD7 1DP, UK. d.connah@bradford.ac.uk.
authors.forename: David
authors.initials: D
authors.lastname: Connah
authors.affiliation: Information and Communications Technologies Department, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain. marcelo.bertalmio@upf.edu.
authors.forename: Marcelo
authors.initials: M
authors.lastname: Bertalmío
mesh_terms: D000465:Algorithms; D003116:Color; D003124:Colorimetry / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D010781:Photography / Q000295:instrumentation*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity