2. The characteristics and framework of iCAM
2.1. Characteristics of iCAM
In 2002, Munsell Color Science Lab of Rochester Institute of Technology put forward iCAM (Image Color Appearance
Model), which integrates advantages of IPT Color Space (hue uniformity) [2], S-CIELAB Color Space (spatial filter) [3] and
CIECAM02 Color Appearance Model (Chromatic Adaptation Transformation) [4,5] whose target is to simultaneously provide
traditional color appearance capabilities, spatial vision attributes, and color difference metrics. iCAM has the following
characteristics.
Since the consideration of practical viewing conditions has been involved in iCAM, it can accurately predict the result of
the observation under different conditions.
Its hue uniformity is excellent. As iCAM can describe aspects of color appearance phenomena including accurate metrics
of color differences well, it can be used to carry out the color gamut mapping calculation based on the perception of human
eyes.
iCAM considers image’s spatial aspects of vision and adaptation. The adapting stimulus becomes a spatially low-pass
image. So it is adapted to images.
Therefore, we selected iCAM as the standard color model of CMS. The color gamut mapping calculation from input
media to output media can be accomplished in the iCAM. Thus, the computer vision after cross-media transmission is more
approximate to human vision.
2.2. The mechanism of creating the color gamut mapping platform [6–8]
The structure of the iCAM standard model is mainly divided into two parts. Firstly, for Chromatic Adaptation
Transformation (CAT), the XYZ tristimulus values are converted into CAT02 color space. Then X
0Y
0
Z
0
, which has accomplished
the chromatic adaptation are converted into IPT (Image Processing Transform) color space to carry out the gamut mapping
calculation. Finally, these values are inversely converted to X
00Y
00Z
00. The process of creating the IPT color gamut mapping
platform is shown in Fig