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We present a novel algorithm for image fusion from irregularly sampled data. The method is based on the framework of normalized convolution (NC), in which the local signal is approximated through a projection onto a subspace. The use of polynomial basis functions in this paper makes NC equivalent to a local Taylor series expansion. Unlike the traditional(More)
—In this paper, we present a stable, recursive algorithm for the Gabor filter that achieves—to within a multiplicative constant—the fastest possible implementation. For a signal consisting of samples, our implementation requires () multiply-and-add (MADD) operations, that is, the number of computations per input sample is constant. Further, the complexity(More)
An edge detection scheme is developed robust enough to perform well over a wide range of signal-to-noise ratios. It is based upon the detection of zero crossings in the output image of a nonlinear Laplace filter. Specific characterizations of the nonlinear Laplacian are its adaptive orientation to the direction of the gradient and its inherent masks which(More)
In this paper, we present a novel method to estimate curvature of iso gray-level surfaces in gray-value images. Our method succeeds where standard isophote curvature estimation methods fail. There is neither a segmentation of the surface needed nor a parametric model assumed. Our estimator works on the orientation field of the surface. This orientation(More)
Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of(More)
In this paper we describe a new strategy for using local structure adaptive filtering in normalized convolution. The shape of the filter, used as the applicability function in the context of normalized convolution, adapts to the local image structure and avoids filtering across borders. The size of the filter is also adaptable to the local sampling density(More)
ÐCurved oriented patterns are dominated by high frequencies and exhibit zero gradients on ridges and valleys. Existing curvature estimators fail here. The characterization of curved oriented patterns based on translation invariance lacks an estimation of local curvature and yields a biased curvature-dependent confidence measure. Using parameterized(More)