8 February 2005 Implementing color transformation across media based on color appearance model by neural networks
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Interest in color appearance models (CAM) has been greatly stimulated recently by the need in handling digital images. This article demonstrates that a multi-layers feed-forward artificial neural network with the error back-propagation algorithm was used to approximate color appearance model CIECAM02 with different white points and different media. For the prediction of the forward and inverse model respectively, in order to realize accurate mapping, especially to the inverse model, color spaces conversion between input color space and output color space (that is cylindrical coordinates and rectangular coordinates) was implemented before training the neural networks. Meanwhile we approximated the combination of the forward and inverse CIECAM02 models employing a neural network for different conditions including whites (D65 or D50) and media (booth and CRT) in order to realize the color transformation from one medium to another conveniently. The experimental results indicated that the prediction could satisfy the accuracy requirement. So in practice we can choose these two kinds of different prediction ways to meet our need according to different situations.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Binghua Chai, Binghua Chai, Ningfang Liao, Ningfang Liao, Dazun Zhao, Dazun Zhao, } "Implementing color transformation across media based on color appearance model by neural networks", Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.570757; https://doi.org/10.1117/12.570757

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