Thevenaz, PhilippeSage, DanielUnser, Michael2013-02-272013-02-272013-02-27201210.1109/Tip.2012.2200903https://infoscience.epfl.ch/handle/20.500.14299/89605WOS:000307896800009Edge-preserving smoothers need not be taxed by a severe computational cost. We present, in this paper, a lean algorithm that is inspired by the bi-exponential filter and preserves its structure-a pair of one-tap recursions. By a careful but simple local adaptation of the filter weights to the data, we are able to design an edge-preserving smoother that has a very low memory and computational footprint while requiring a trivial coding effort. We demonstrate that our filter (a bi-exponential edge-preserving smoother, or BEEPS) has formal links with the traditional bilateral filter. On a practical side, we observe that the BEEPS also produces images that are similar to those that would result from the bilateral filter, but at a much-reduced computational cost. The cost per pixel is constant and depends neither on the data nor on the filter parameters, not even on the degree of smoothing.Bi-exponential filterbilateral filternonlocal meansrecursive filterCIBM-SPtext::journal::journal article::research article