Fast Algorithms for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive implementation of the Gaussian filter
Signal Processing
Recursive implementation of LoG filtering
Real-Time Imaging
Recursive Gaussian Derivative Filters
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
IEEE Transactions on Signal Processing
Boundary conditions for Young-van Vliet recursive filtering
IEEE Transactions on Signal Processing - Part I
Proceedings of the Conference on Design, Automation and Test in Europe
On the computational benefit of tensor separation for high-dimensional discrete convolutions
Multidimensional Systems and Signal Processing
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Gaussian smoothing filters and Gaussian derivative filters can be estimated by recursive IIR filters, as shown by Deriche [3, 4]. The design of those filters does, however, not enforce the important property that derivative filters should have an exactly zero DC-response. This article extends the theory in [4] to take this constraint into account without loss of performance and also gives new compact closed form expressions for the normalization factors required for proper scaling of the filter responses.