A new algorithm for calculating perceived colour difference of images

Faithful colour reproduction of digital images requires a reliable measure to compare such images in order to evaluate the reproduction performance. The conventional methods attempt to apply the CIE Colorimetry based colour difference equations, such as CIELAB, CMC, CIE94 and CIEDE2000, to complex images on a pixel-by-pixel basis, and calculates the overall colour difference as the averaged difference of each pixel in the image. This method is simple and straightforward but often does not represent the colour difference perceived by human visual system. This paper proposes a new algorithm for calculating the overall colour difference between a reproduced image and its original. The results obtained show that this new metric provides a quantitative measure that more closely corresponds to the colour difference perceived by human visual system

A study of digital camera colorimetric characterisation based on polynomial modelling

The digital camera is a powerful tool to capture images for use in image processing and colour communication. However, the RGB signals generated by a digital camera are device-dependent, i.e. different digital cameras produce different RGB responses for the same scene. Furthermore, they are not colorimetric, i.e. the output RGB signals do not directly correspond to the device-independent tristimulus values based on the CIE standard colorimetric observer. One approach for deriving a colorimetric mapping between camera RGB signals and CIE tristimulus values uses polynomial modelling and is described here. The least-squares fitting technique was used to derive the coefficients of 3× n polynomial transfer matrices yielding a modelling accuracy typically averaging 1 Δ E units in CMC(1:1) when a 3× 11 matrix is used. Experiments were carried out to investigate the repeatability of the digitising system, characterisation performance when different polynomials were used, modelling accuracy when 8-bit and 12-bit RGB data were used for characterisation and the number of reference samples needed to achieve a reasonable degree of modelling accuracy. Choice of characterisation target and media and their effect on metamerism have been examined. It is demonstrated that a model is dependent upon both media and colorant and applying a model to other media/colorants can lead to serious eye-camera metamerism problems