Title :
Hierarchical recursive running median
Author_Institution :
Comput. Vision & Remote Sensing, Tech. Univ. Berlin, Berlin, Germany
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
Median filter was long known in image processing for its high computational costs. Recently, an algorithm was developed which is able to compute median on integer-valued images in a roughly constant average time. A new O(1) algorithm presented here further improves the aforementioned one, being at the time of writing the lowest theoretical complexity algorithm for calculation of 2D and higher dimensional median filters. The algorithm scales naturally to higher precision (e.g. 16-bit) integer data without any modifications. Its adaptive version offers additional speed-up for images showing compact modes in gray-value distribution. The algorithm will be useful for high bit depth data or on hardware without SIMD extensions. A C/C++ implementation is available under GPL for research purposes.
Keywords :
C++ language; computational complexity; image processing; median filters; C-C++ implementation; O(1) algorithm; SIMD extension; complexity algorithm; gray-value distribution; hierarchical recursive running median filter; image processing; integer-valued image; single instruction multiple data; Approximation algorithms; Computational complexity; Histograms; Runtime; Signal processing algorithms; Vegetation; computational complexity; computational efficiency; filtering algorithms; nonlinear filters;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6466807