A more complete description of information decomposition in both scale and spatial coordinates can be found in the hypertext article: [Jag ICCV 95] . Also availible in postscript (2MB).
At an early stage in processing images it would be useful to know in what scales relevant information occurs. We use an information theoretic measure of how much information an image contains given an observer observing at a particular resolution. This is then decomposed into succesive contrasts between a series of resolution lengths. We have made experiments showing that this measure gives clear indication of characteristic scale lengths of objects in a variety of real world images.
For example, consider this image of a toy town, "Tinytown" In this image we can se structure on the macroscopic level (bars, trees, houses etc..), but there is also structure at a much smaller scale, corresponding to the textures of the ground and trees. (You may need a good monitor to see this ;). The bimodal structure of the scale space information expansion shown below accurately tells us about these two scales present in the image.
The end result of the attention selection, passed on for further processing, is a few selected ROI's and their scale space information.
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