出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Endoscopic color imaging technology has been a great improvement to assist clinicians in
making better decisions since the initial introduction. In this study, a novel combined
method, including quadratic objective functions for the dichromatic model by Krebs et al.
and Wyszecki`s spectral decomposition theory and the well-known principal component
analysis technique is employed. New algorithm method working for color space converting
of a conventional endoscopic color image, as a target image, with a Narrow Band Image
(NBI), as a source image.
The images of the target and the source are captured under known illuminant/sensor/filters
combinations, and matrix Q of the decomposition theory is computed for such
combinations. The intrinsic images which are extracted from the Krebs technique are
multiplied by the matrix Q to obtain their corresponding fundamental stimuli. Subsequently,
the principal component analysis technique was applied to the obtained fundamental
stimuli in order to prepare the eigenvectors of the target and the source. Finally, the first
three eigenvectors of each matrix were then considered as the converting mapping matrix.
The results precisely seem that the color gamut of the converted target image gets closer to
the NBI image color gamut.
