
doi: 10.1007/bf00364135
A conceptually simple and logically consistent version of ``scale-space'' for the temporal domain is proposed. The method does not violate temporal causality, yet conserves causality in the resolution domain at any given moment in time. The filter kernels are not Gaussians (that would certainly lead to a violation of temporal causality) but are related to the Gaussians via a simple transformation of the time axis. They depend on a pair of parameters, one that has the character of a temporal delay and one that specifies the temporal resolution. In the limit for long delays (but fixed resolution) these kernels asymptotically approach the Gaussian again. Extensions of the theory towards a scale space-time are discussed.
causality, Psychophysics and psychophysiology; perception, Other natural sciences (mathematical treatment), Gaussian kernels, Filtering in stochastic control theory, image processing, filter kernels, artificial vision, scale-space, scale space-time, mammalian visual systems, temporal domain
causality, Psychophysics and psychophysiology; perception, Other natural sciences (mathematical treatment), Gaussian kernels, Filtering in stochastic control theory, image processing, filter kernels, artificial vision, scale-space, scale space-time, mammalian visual systems, temporal domain
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