Robust method of edge detection
Maria Petrou, Josef Kittler · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
We present here the theory of developing robust test statistics for edge shape matching in one dimensional signals. We show that an unbiased test can be developed under the assumption of uncorrelated noise and this test can be made optimal and robust to perturbations of the assumed noise distribution under the extra assumption of symmetric noise. This approach to edge detection is believed to overcome the shortcomings of the uncertainty principle in image processing and is appropriate for use when edges of a certain type have to be identified with great accuracy in their location.