6533b839fe1ef96bd12a6326

RESEARCH PRODUCT

Application of Adaptive Hypergraph Model to Impulsive Noise Detection

Hocine CherifiAlain BrettoSoufiane RitalDriss Aboutajdine

subject

Scheme (programming language)NoiseHypergraphSignal-to-noise ratioComputer scienceImage processingGraph theoryNoise detectionAlgorithmcomputercomputer.programming_languageImage (mathematics)

description

In this paper, using hypergraph theory, we introduce an image model called Adaptive Image Neighborhood Hypergraph (AINH). From this model we propose a combinatorial definition of noisy data. A detection procedure is used to classify the hyperedges either as noisy or clean data. Similar to other techniques, the proposed algorithm uses an estimation procedure to remove the effects of the noise. Extensive simulations show that the proposed scheme consistently works well in suppressing of impulsive noise.

yearjournalcountryeditionlanguage
2001-01-01
https://doi.org/10.1007/3-540-44692-3_67