Information Theory in Computer Vision and Pattern Recognition

The connections between information theory and computer vision have long been appreciated. Vision can be considered to be a decoding problem where the encoding of the information is performed by the physics of the world – by light rays striking objects and being reflected to cameras or eyes. Ideal observer theories were pioneered by scientists such as Horace Barlow to compute the amount of information available in the visual stimuli, and to see how efficient humans are at exploiting it. But despite the application of information theory to specific visual tasks, there has been no attempt to bring all this work together into a clear conceptual framework.