Abstract:

 Laplace operator is apt to be affected by noise. An edge detection algorithm finite ridgelet transform (FRIT)-based was proposed in order to improve it. Based on Laplace probability distribution function (PDF), the finite ridgelet-based transform coefficients were analyzed, and the maximum a posteriori (MAP) estimation for FRIT coefficients was developed. According to the model for some edge detectors, an optimal threshold for edge detection was obtained, and edge image was extracted. Both avoiding the effect of noise and preserving edge image were achieved. Experiments results showed that the proposed edge detector achieved better performances both on the localization and avoiding the effect of noise, edge image could be better distinguished by the proposed method.

Key words:  finite ridgelet transform, edge detection, Laplace operator, maximum a posteriori estimation