Title :
A noise cancellation algorithm based on hypergraph modeling
Author :
Bretto, A. ; Cherifi, H.
Author_Institution :
Lab. de Traitement du Signal et Instrum., GIAT Ind., Saint-Etienne, France
Abstract :
Although the binary relations used in proximity graphs are relevant for many basic situations, they cannot represent the structuration process of digital images. In this paper we show that hypergraph theory is a more appropriate frame to describe the neighborhood relations that can be formalized between pixels. We illustrate the effectiveness of such a model by deriving a noise cancellation algorithm based on a basic combinatoric property of hypergraphs
Keywords :
Gaussian noise; filtering theory; graph theory; image processing; Helly algorithm; additive Gaussian noise; binary relations; combinatoric property; digital images; filters; hypergraph modeling; image analysis; neighborhood relations; noise cancellation algorithm; pixels; proximity graphs; Artificial intelligence; Computational geometry; Computer science; Image edge detection; Image processing; Mathematical model; Mathematics; Noise cancellation; Pattern analysis; Pattern recognition;
Conference_Titel :
Digital Signal Processing Workshop Proceedings, 1996., IEEE
Conference_Location :
Loen
Print_ISBN :
0-7803-3629-1
DOI :
10.1109/DSPWS.1996.555446