An information theory analysis of visual complexity and dissimilarity.
The subjective complexity of a computer-generated bitmap image can be measured by magnitude estimation scaling, and its objective complexity can be measured by its compressed file size. There is a high correlation between these measures of subjective and objective complexity over a large set of marine electronic chart and radar images. The subjective dissimilarity of a pair of bitmap images can be predicted from subjective and objective measures of the complexity of each image, and from the subjective and objective complexity of the image produced by overlaying the two simple images. In addition, the subjective complexity of the image produced by overlaying two simple images can be predicted from the subjective complexity of the simple images and the subjective dissimilarity of the image pair. The results of the experiments that generated these complexity and dissimilarity judgments are consistent with a theory, outlined here, that treats objective and subjective measures of image complexity and dissimilarity as vectors in Euclidean space.
Donderi
Don C
DC
i Department of Psychology, McGill University, 1205 Dr Penfield Avenue, Montr6al, QC H3A 1B1, Canada. don.donderi@mcgill.ca
D003198:Computer Simulation; D006801:Humans; D007257:Information Theory; D007600:Judgment; D008962:Models, Theoretical; D010775:Photic Stimulation; D014794:Visual Fields; D014796:Visual Perception