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A combinatorial based technique for impulsive noise removal in images

Rital S., Bretto A., Cherifi H., Aboutajdine D.

Image Processing & Communications

2001

Vol. 7, no 3-4

115-129

The aim of this work is the elimination of the impulsive noise from an image 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 hyperedges either as noisy or clean data. Similar to other techniques, the proposed algorithm uses an estimation procedure to remove the effects of noise. The efficiency of the proposed method was tested on gray scale images using objective image quality measures. The results show that the new method outperforms standard impulsive noise reduction algorithms.