Information theoretic measure for visual target distinctness

It is of great benefit to have advance knowledge of human visual target acq uisition performance for targets or other relevant objects. However, search performance inherently shows a large variance and depends strongly on prio r knowledge of the perceived scene. A typical search experiment therefore r equires a large number of observers to obtain statistically reliable data. Moreover, measuring target acquisition performance in field situations is u sually impractical and often very costly or even dangerous. This paper pres ents a new method for characterizing information of a target relative to it s background. The resultant computational measures are then applied to quan tify the visual distinctness of targets in complex natural backgrounds from digital imagery. A generalization of the Kullback-Leibler joint informatio n gain of various random variables is shown to correlate strongly with visu al target distinctness as estimated by human observers. Bootstrap methods f or assessing statistical accuracy were used to produce this inference.