A new model (called multi-component blurring or MCB) to account for image blurring effects due to depth discontinuities is presented. We show that blurring processes operating in the vicinity of large depth discontinuities can give rise to emergent image details, quite distinguishable but nevertheless un-explained by previously available blurring models. In other words, the maximum principle for scale space [Per90] does not hold. It is argued that blurring in high-relief 3-D scenes should be more accurately modeled as a multi-component process. We present results form extensive and carefully designed experiments, with many images of real scenes taken by a CCD camera with typical parameters. These results have consistently support our new blurring model. Due care was taken to ensure that the image phenomena observed are mainly due to de-focussing and not due to mutual illuminations [For89], specularity [Hea87], objects’ “finer” structures, coherent diffraction, or incidental image noises. [Gla88] We also hypothesize on the role of blurring on human depth-from-blur perception, based on correlation with recent results from human blur perception. [Hes89].
CITATION STYLE
Nguyen, T. C., & Huang, T. S. (1992). Image blurring effects due to depth discontinuitites: Blurring that creates emergent image details. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 588 LNCS, pp. 347–362). Springer Verlag. https://doi.org/10.1007/3-540-55426-2_39
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