Restoration of Biomedical Images using Locally Adaptive B-Spline Smoothing

In this paper we present an adaptive B-spline smoothing algorithm to reduce noise in biomedical images. The filter consists of a convolution between the input image and an adaptive B-spline kernel that varies its size according to the local image characteristics. We show that this filter can be efficiently implemented by taking advantage of the convolution and factorization properties of B-splines. We tested our filter on phantoms and real images, obtaining very high noise reduction in homogeneous areas with little degradation of the edges.