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What and Who

Median Filtering is Equivalent to Sorting

Jukka Suomela
Aalto University
Talk

Jukka Suomela (https://users.ics.aalto.fi/suomela/) is an Assistant Professor in the Department of Computer Science at Aalto University. He received his PhD from the University of Helsinki in 2009, and the title of Docent in Computer Science in 2012. Suomela's research group (http://research.ics.aalto.fi/da/) conducts basic research related to the theoretical foundations of distributed computing, with particular emphasis on the concept of locality in the context of distributed graph algorithms.
AG 1, AG 2, AG 3, AG 4, AG 5, RG1, SWS, MMCI  
MPI Audience
English

Date, Time and Location

Wednesday, 11 March 2015
13:00
30 Minutes
E1 4
024
Saarbrücken

Abstract

In this talk I will show that the following problems are equivalent,
both in theory and in practice:

(1) median filtering: given an n-element vector, compute the sliding
window median with window size k,

(2) piecewise sorting: given an n-element vector, divide it in n/k
blocks of length k and sort each block.

By prior work, median filtering is known to be at least as hard as
piecewise sorting: with a single median filter operation we can sort
θ(n/k) blocks of length θ(k). Our recent work shows that median
filtering is also as easy as piecewise sorting: we can do median
filtering with one piecewise sorting operation and linear-time
postprocessing; moreover, the algorithm is very efficient in practice.

See http://arxiv.org/abs/1406.1717 for more information.

Contact

Christoph Lenzen
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Christoph Lenzen, 02/26/2015 10:30 -- Created document.