Discontinuity Detection and Thresholding-A Stochastic Approach

We study discontinuity detection and thresholding using a stochastic approach. We discuss a general form of detectors, which includes a number of well known detectors as special cases. Thresholding is indispensable to eliminate spurious responses from the detection process. We propose a Weighted Thresholding, which is designed to cope with a variety of anomalies. Our analysis and experimental results on real images show that intelligent thresholding methods can make a significant difference for discontinuity detection.