Generalized adaptive smoothing for multiscale edge detection

Discontinuity preserving smoothing for edge detection is receiving more attention because of the fact that it does not suffer the disadvantage of linear filtering which smooth edges as well as noise. Adaptive smoothing is basically a discontinuity preserving smoothing scheme which preserves edges with gradient magnitude greater the preset threshold value. However, it suffers a leaking effect in its long term iterative behavior. The propagation of smoothing in the low contrast area will sometimes affect the preservation of high contrast edges. This paper proposes a remedy for adaptive smoothing which includes the original image in the iteration process. It provides not only a more stable iterative behavior, but also introduces a new scaling parameter which facilitates multiple scale processing. The study of iterative behavior of the proposed generalized adaptive smoothing as well as automatic selection of the number of iterations is presented.