This paper presents a new method for computing the Feature-adapted Radon and Beamlet transforms [1] in a
fast and accurate way. These two transforms can be used for detecting features running along lines or piecewise
constant curves. The main contribution of this paper is to unify the Fast Slant Stack method, introduced in
[2], with linear filtering technique in order to define what we call the Feature-adapted Fast Slant Stack. If
the desired feature detector is chosen to belong to the class of steerable filters, our method can be achieved in
O(N log(N)), where N = n2 is the number of pixels. This new method leads to an efficient implementation of
both Feature-adapted Radon and Beamlet transforms, that outperforms our previous works [1] both in terms
of accuracy and speed. Our method has been developed in the context of biological imaging to detect DNA
filaments in fluorescent microscopy.
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