The problem of detecting edges in noisy digitized images is considered. A stochastic model of edge structure is proposed and the edge detection problem formulated as one of least mean-square spatial filtering. The resulting filtering structures are implemented as two-dimensional recursive digital filters. Computer experiments with this class of edge detectors will be described. The results indicate substantial advantages over conventional edge detectors in the presence of noise. Applications to real-world imagery data are discussed.
|Title of host publication||Comput Graphics Image Process|
|Number of pages||25|
|State||Published - Oct 1 1977|
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