Abstract
We present two effective algorithms for removing impulse noise from color images. Our proposed algorithms take a two-step approach: in the first step, noise color pixel candidates are identified by an impulse detector, and in the second step, only those identified noise candidates in the image are restored by using a modified weighted vector median filter. Extensive experiments indicate that our proposed algorithms have good performance, and are more effective than most of the existing algorithms in removing impulse noise from color images.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Astola, J., Haavisto, P., Neuvo, Y.: Vector median filters. Proc. IEEE 78, 678–689 (1990)
Astola, J., Kuosmanen, P.: Fundamentals of Nonlinear Digital Filtering. CRC, Boca Raton (1997)
Chan, R.H., Ho, C.W., Nikolova, M.: Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization. IEEE Trans. Image Process. 14, 1479–1485 (2005)
Cheng, L., Hou, Z.-G., Tan, M.: Relaxation labeling using an improved hopfield neural network. In: Huang, D.-S., Li, K., Irwin, G.W. (eds.) Intelligent Computing in Signal Processing and Pattern Recognition. LNCIS, vol. 345, pp. 430–439. Springer, Heidelberg (2006)
Dong, Y., Chan, R.H., Xu, S.: A detection statistic for random-valued impulse noise. IEEE Trans. Image Process. 16, 1112–1120 (2007)
Gonzalez, R., Woods, R.: Digital Image Processing, 3rd edn. Addison-Wesley, Boston (1993)
Gabbouj, M., Cheickh, F.A.: Vector median-vector directional hybrid filter for color image restoration. In: Proceedings of EUSIPCO-96, pp. 879–881 (1996)
Jin, L., Li, D.: An efficient color-impulse detector and its application to color images. IEEE Signal Process. Lett. 14, 397–400 (2007)
Khryashchev, V., Kuykin, D., Studenova, A.: Vector median filter with directional detector for color image denoising. In: Proceedings of the World Congress on Engineering (London), vol. 2 (2011)
Karakos, D.G., Trahanias, P.E.: Generalized multichannel image-filtering structures. IEEE Trans. Image Process. 6, 1038–1045 (1997)
Lukac, R.: Adaptive vector median filtering. Pattern Recognit. Lett. 24, 1889–1899 (2003)
Lukac, R., Plataniotis, K.N., Venetsanopoulos, A.N., Smolka, B.: A statistically-switched adaptive vector median filter. J. Intell. Robot. Syst. Theory Appl. 42, 361–391 (2005)
Lukac, R., Smolk, B., Plataniotis, K.N.: Sharpening vector median filters. Signal Process. 87, 2085–2099 (2007)
Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector filtering for color imaging. IEEE Signal Process. Mag. 22, 74–86 (2005)
Plataniotis, K.N., Androutsos, D., Venetsanopoulos, A.N.: Color image processing using adaptive vector directional filters. IEEE Trans. Circ. Syst. II(45), 1414–1419 (1998)
Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Berlin (2000)
Trahanias, P.E., Karakos, D.G., Venetsanopoulos, A.N.: Directional processing of color images: theory and experimental results. IEEE Trans. Image Process. 5, 868–880 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Zhang, Jj., Zhang, Jl., Gao, M. (2017). Two Effective Algorithms for Color Image Denoising. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-68345-4_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68344-7
Online ISBN: 978-3-319-68345-4
eBook Packages: Computer ScienceComputer Science (R0)