A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms

Abstract

The proliferation of low‐cost colour imaging devices in the consumer market has led to a greater need to transfer images from one medium or device to another without loss of colour fidelity. A common solution is to characterise each device in terms of its CIE tristimulus values. In this paper two general techniques, artificial neural networks and polynomial transforms, are compared for their usefulness in characterising colour cameras. The neural and polynomial techniques are shown to give approximately similar performance once the parameters of the models are optimised. Since neural networks can be difficult and time‐consuming to train, it is concluded that polynomial transforms offer the better alternative for camera characterisation.