Soft-Switching Adaptive Technique of Impulsive Noise Removal in Color Images

In this paper an adaptive filtering technique for impulsive noise reduction in color images is presented. The noise detection algorithm is based on the concept of aggregated distances assigned to the pixels belonging to the filtering window. The value of the difference between the accumulated distance assigned to the central sample and to the pixel with the lowest rank, is used as an indicator of the strength of impulses injected into the image by the noise process. The output of the proposed filter is a weighted mean of the central pixel and the vector median of samples in the filtering window. The new filter outperforms existing designs for low noise contamination and can be used in various applications in which the detail preserving noise reduction is required.

[1]  Rastislav Lukac,et al.  Adaptive vector median filtering , 2003, Pattern Recognit. Lett..

[2]  Hassan A. Kingravi,et al.  Nonlinear vector filtering for impulsive noise removal from color images , 2007, J. Electronic Imaging.

[3]  Andrzej Chydzinski,et al.  Fast detection and impulsive noise removal in color images , 2005, Real Time Imaging.

[4]  Jaakko Astola,et al.  Nonlinear multivariate image filtering techniques , 1995, IEEE Trans. Image Process..

[5]  Rastislav Lukac,et al.  Adaptive video filtering framework , 2004, Int. J. Imaging Syst. Technol..

[6]  Alexander A. Sawchuk,et al.  Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Konstantinos N. Plataniotis,et al.  Self-adaptive algorithm of impulsive noise reduction in color images , 2002, Pattern Recognit..

[8]  K. Martin,et al.  Vector filtering for color imaging , 2005, IEEE Signal Processing Magazine.

[9]  Rastislav Lukac,et al.  Adaptive Color Image Filtering Based on Center-Weighted Vector Directional Filters , 2004, Multidimens. Syst. Signal Process..

[10]  K. Plataniotis,et al.  Color Image Processing and Applications , 2000 .

[11]  Panos E. Trahanias,et al.  Vector directional filters-a new class of multichannel image processing filters , 1993, IEEE Trans. Image Process..

[12]  J. Astola,et al.  Vector median filters , 1990, Proc. IEEE.

[13]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Rastislav Lukac,et al.  Selection weighted vector directional filters , 2004, Comput. Vis. Image Underst..

[15]  Kenneth E. Barner,et al.  Nonlinear Signal and Image Processing: Theory, Methods, and Applications , 2003 .

[16]  Ioannis Pitas,et al.  Nonlinear Digital Filters - Principles and Applications , 1990, The Springer International Series in Engineering and Computer Science.

[17]  Rastislav Lukac,et al.  Fast adaptive similarity based impulsive noise reduction filter , 2003, Real Time Imaging.

[18]  Bogdan Smolka.  On the Adaptive Impulsive Noise Attenuation in Color Images , 2006, ICIAR.

[19]  Anastasios N. Venetsanopoulos,et al.  Nonlinear Techniques for Color Image Processing , 2003 .

[20]  Moncef Gabbouj,et al.  Adaptive L-filters with applications in signal and image processing , 1994, Signal Process..

[21]  Rastislav Lukac,et al.  Optimised directional distance filter , 2002 .

[22]  Ioannis Pitas,et al.  Multivariate ordering in color image filtering , 1991, IEEE Trans. Circuits Syst. Video Technol..