Gamma-Compression Gamut Mapping method based on the concept of Image-to-Device

This article proposes Gamma-Compression Gamut Mapping Algorithm (GMA) based on the concept of Image-to-Device. Considering the relations of color gamu t boundaries between the devices (such as printer, monitor) and image sourc e. the proposed method adjusts the image color distributions, fitting to th e output device gamut. The proposed image-to-device GMA works to preserve i ts gradation and chroma with minimum losses depending on the color distribu tions in the segmented hue-leaves. The following three typical mapping meth ods are compared and discussed: (1) Device-to-Device Gamma-Compression GMA, (2) Image-to-Device Gamma-Compression GMA; (3) Clipping GMA. Two kinds of color spaces, CIEL*a*b* and CIECAM97s-JCh, are used for testing these GMAs. The psychophysical experiments in CIECAM97s-JCh space resulted in better r endition than did CIEL*a*b* space. In natural color imaging applications, t he proposed Image-to-Device GMA is superior to conventional Device-to-Devic e GMA, and is a better way to maintain its gradation and higher chroma.