Adaptation of colour perception through dynamic ICC profile modification : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Albany (Auckland), New Zealand

Abstract

Digital colour cameras are dramatically falling in price, making them affordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness.

Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction -- such as (ICC based) colour management -- characterise a capturing device under given conditions through an input device profile. This profile can be applied to correct for deviating colour perception. But this profile is only valid for the specific conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and artificial sources (incandescent or fluorescent lamps).

Colour measurements for colour based reasoning need to be represented in a robustly defined way. One such suitable and well defined description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC profile are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modified to operate on Lab colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples.

We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a first order Taylor approximation (affine transformation). By performing a multi-dimensional linear regression analysis on the tracked data points, parameterisations for the affine transformations were derived.

Finally, the device profile is updated by amalgamating the corrections from the model into the ICC profile for a single, comprehensive transformation. Following applications of the ICC based colour profiles are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive profile adaptation generally showed to be usable for many frames.

The goal was to set out and find a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.