Application of Adaptive Hypergraph Model to Impulsive Noise Detection

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.

• Type: Conference
• Year: 2001
• Where: CAIP
• Authors: Soufiane Rital, Alain Bretto, Driss Aboutajdine, Hocine Cherifi
• Keywords: CAIP 2001, Hypergraph Theory, Image Analysis, Image Neighborhood Hypergraph, Noisy Data