Journal of Electronic ImagingGaussian mixture model for edge-enhanced images
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In this paper we present a new stochastic model for pixels in an edge-enhanced image. The model is robust because it allows for the possibilities of false and multiple edges, and may be efficiently estimated using an expectation-maximization technique with a minimum description length metric. The direct applicability of the model for the sequential edge linking algorithm is investigated and shown to improve edge detection for low signal-to-noise ratio cases.