 The Impact of Order Statistics on Signal ProcessingAlan C. Bovik and Scott T. Acton Chapter 14 in Statistical Theory and Applications, 1996, pp 153-176 from Springer Abstract: Abstract In signal processing, the use of order statistics has been quite profitable. Nonlinear filters based on order statistic techniques have enabled signal processors to enhance and restore corrupted digital information. The first such device, the median filter, improved upon linear filtering methods by providing signal impulse rejection without the destruction of important signal properties. More general order statistic filter paradigms were then developed that could be tailored to certain signal characteristics and noise processes. Because the basic order statistic filters ignore temporal and spatial signal ordering, extensions such as the stack, C, Ll, WMMR, and permutation filters were created. Finally, order statistics have been applied to several important signal processing problems such as image morphology, edge detection, signal enhancement and signal restoration. This contribution attempts to summarize a few of the landmark innovations in signal processing that have been made possible through the adoption of order statistics. Keywords: Order statistic filters; signal processing; image processing (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-3990-1_14 Ordering information: This item can be ordered from DOI: 10.1007/978-1-4612-3990-1_14 Access Statistics for this chapter More chapters in Springer Books from Springer |
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