We propose two methods for controlling the acquisition of images using a camera/digitiser combination which seek to make good use of the dynamic range of the digitiser. The system controls are the black and white reference levels of the digitiser, and the exposure time of the CCD sensor. We use the grey level histogram to characterise the level of control.
Both methods use models of the camera/digitiser and of the grey level distribution in the scene. These allow control values that will achieve a given result to be predicted from the current grab and used on the next one. Thus the methods use feed forward control, taking advantage of the models to achieve a fast response. The first method, pragmatic, attempts to adjust the controls to achieve target values of histogram position and scale. The second method, information theoretic seeks to maximise the information content of the histogram as measured by the entropy. An advantage of the information theoretic method is that it produces a single measure of performance. This we use in a strategy for including the exposure variable in the control system. Having a single measure avoids the difficult problem of choosing rather arbitrary weighting factors for the position and scale errors in the pragmatic method.
We test both methods using stored images and simulating various grab conditions. Both methods perform well, resulting in effective control values from simulated grabs containing significant saturation. We test the second method on line using real grabs and show fast and accurate recovery from disturbances of illumination and scene content.