Image Salt & Pepper Noise Self-adaptive Suppression Algorithm Based on Similarity Function
Song Kun Yu, Mantian Li, Lining Sun · Acta Automatica Sinica · 2007
Through summarizing the existing detail-preserving salt & pepper noise suppression methods, a new similarity function self-adaptive weighted algorithm is proposed. It analyzes and overcomes the shortcoming of the local extremum misjudgment of the Maximum-minimum noise detector by using a similarity function self-adaptive weighted algorithm. The local window noise probability is estimated by applying extremum trimming operation to select a suitable flltering window (recursive window or non-recursive window). Thus the proposed algorithm realizes self-adaptive suppression of difierent salt & pepper noise probabilities using a 3£3 flltering window. Experiments show that the results of salt & pepper noise suppression, detail-preserving and computation e-ciency are satisfactory.