Detail-Preserving Regularization Based Removal of Impulse Noise from Highly Corrupted Images

Authors:
Bogdan Kwolek
Affiliations:
Rzeszów University of Technology, Computer and Control Engineering Chair, W. Pola 2, 35-959 Rzeszów, Poland
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Year:
2007

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Abstract

This paper proposes a new filtering scheme for eliminating random-valued impulse noise from gray images. In the first phase a noise detector is utilized to extract the noise candidates. Next, the algorithm applies a connected component analysis in order to gather the neighboring noisy pixels into separate sets of connected noise candidates. The corrupted pixels are restored using a detail preserving regularization method. The main idea of the proposed approach is to gather the noisy candidate pixels into separate sets of connected pixels and solve the minimization functional over these pixels. Experimental results illustrate the efficiency and effectiveness of the algorithm.