Applying generic programming to image processing

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Abstract

This paper presents the evolution of algorithms implementation in image processing libraries and discusses the limits of these implementations in terms of reusability. In particular, we show that in C++, an algorithm can have a general implementation; said differently, an implementation can be generic, i.e.independent of both the input aggregate type and the type of the data contained in the input aggregate. A total reusability of algorithms can therefore be obtained; moreover, a generic implementation is more natural and does not introduce a meaningful additional cost in execution time as compared to an implementation dedicated to a particular input type.


Bibtex (lrde.bib)

@InProceedings{	  geraud.01.ai,
  author	= {Thierry G\'eraud and Yoann Fabre and Alexandre Duret-Lutz},
  title		= {Applying generic programming to image processing},
  booktitle	= {Proceedings of the IASTED International Conference on
		  Applied Informatics (AI)---Symposium on Advances in
		  Computer Applications},
  year		= 2001,
  publisher	= {ACTA Press},
  editor	= {M.H.~Hamsa},
  address	= {Innsbruck, Austria},
  pages		= {577--581},
  month		= feb,
  project	= {Olena},
  abstract	= {This paper presents the evolution of algorithms
		  implementation in image processing libraries and discusses
		  the limits of these implementations in terms of
		  reusability. In particular, we show that in C++, an
		  algorithm can have a general implementation; said
		  differently, an implementation can be generic, i.e.,
		  independent of both the input aggregate type and the type
		  of the data contained in the input aggregate. A total
		  reusability of algorithms can therefore be obtained;
		  moreover, a generic implementation is more natural and does
		  not introduce a meaningful additional cost in execution
		  time as compared to an implementation dedicated to a
		  particular input type.}
}