Context-Oriented Image Processing

From LRDE

Abstract

Genericity aims at providing a very high level of abstraction in order, for instance, to separate the general shape of an algorithm from specific implementation details. Reaching a high level of genericity through regular object-oriented techniques has two major drawbackshowever: code cluttering (e.g. class / method proliferation) and performance degradation (e.g. dynamic dispatch). In this paper, we explore a potential use for the Context-Oriented programming paradigm in order to maintain a high level of genericity in an experimental image processing library, without sacrificing either the performance or the original object-oriented design of the application.

Documents

Bibtex (lrde.bib)

@InProceedings{	  verna.15.cop,
  author	= {Didier Verna and Fran{\c{c}}ois Ripault},
  title		= {Context-Oriented Image Processing},
  booktitle	= {Context-Oriented Programming Workshop},
  year		= 2015,
  isbn		= 9781450336543,
  doi		= {10.1145/2786545.2786547},
  abstract	= {Genericity aims at providing a very high level of
		  abstraction in order, for instance, to separate the general
		  shape of an algorithm from specific implementation details.
		  Reaching a high level of genericity through regular
		  object-oriented techniques has two major drawbacks,
		  however: code cluttering (e.g. class / method
		  proliferation) and performance degradation (e.g. dynamic
		  dispatch). In this paper, we explore a potential use for
		  the Context-Oriented programming paradigm in order to
		  maintain a high level of genericity in an experimental
		  image processing library, without sacrificing either the
		  performance or the original object-oriented design of the
		  application. }
}