Abstract
The noise effects in color images are studied from the human perception and machine perception point of view. Three justifiable observations are made to illustrate problems related to individual color signal processing. To minimize the noise effects, two solutions are studied: One is a ‘rental scheme’ and the other is a vector signal processing technique. The ‘rental scheme’ adopts filters originally developed for grey scale images to color images. A set of heuristic criteria is defined to reconstruct an output with minimum artifacts. The vector signal processing technique utilizes a median vector filter based on the well developed median filter for grey scale images. Since the output of the filter does not have the same physical meaning as the median defined in one-dimensional space, the search of a vector median is considered as a minimum problem. The output is guaranteed to be one of the inputs. Both approaches are shown to be very effective in removing speckle noise. Results from real and synthetic images are obtained and compared.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aus, H.M.et al., Computer color vision,Proc. 3rd Internat. Conf. Robot Vision and Sensory Controls, Cambridge, MA pp. 225–229 (1983).
Ballard, D.H. and Brown, C.M.,Computer Vision, Prentice-Hall, Englewood Cliffs (1982).
Buchsbaum, G., A spatial processor model for object color perception,J. Franklin Institute 310, 1–26 (1980).
Cornsweet, T.N.,Visual Perception, Academic Press, New York (1970).
DeValois, R.L., Color vison mechanisms in the monkey,J. Gen. Physiol.,43, 115–128 (1960).
Durrett, H.J.,Color and the Computer, Academic Press, New York (1987).
Gallagher, N. and Wise, G.L., A theoretical analysis of the properties of median filters,IEEE Trans. Acoust. Speech, Signal Process.ASSP-29(6) 1136–1141 (1981).
Healey, G. and Binford, T.O., The role and use of color in a general vision system,Proc. ARPA Image Understanding Workshop, USC (1987).
Horn, B.K.P., Extract reproduction of colored images,Computer Vision, Graphics, and Image Processing 26, 135–167 (1984).
Huang, T.S.,Two-Dimensional Digital Signal Processing II, Springer-Verlag, New York (1981).
Keil, R.E., Machine vision with color detection,Proc. 3rd Internat. Conf. Robot Vision and Sensory Controls, Cambridge, MA, pp. 503–512 (1983).
Kender, J., Saturation, hue and color: Calculation, digitization effects, and use, Technical Report, Department of Computer Science, Carnegie-Mellon University, Pittsburgh, PA (1976).
MacAdam, D.L.,Color Measurement, Theme and Variations, Springer-Verlag, New York (1981).
Nevatia, R., A color edge detector and its use in scene segmentation,IEEE Trans. Systems Man Cybernet.SMC-7(11), 820–826 (1977).
Ohlander, R., Price, K., and Reddy, D.R., Picture segmentation using a recursive region splitting method,Computer Graphics and Image Processing 8, 313–333 (1978).
Ohta, Y., Kanade, T., and Sakai, T., Color information for region segmentation,Computer Graphics and Image Processing 13, 222–241 (1980).
Pratt, W.K.,Digital Image Processing, Wiley, New York (1977).
Richard, H.,Image, Object, and Illusion, Scientific American, Inc. (1974).
Scollar, I., Weidner, B., and Huang, T.S., Image enhancement using and the interquartile distance,Computer Vision, Graphics, and Image Processing 25, 236–251 (1984).
Stabell, U. and Stabell, B., Effects of rod activity on color threshold,Vision Research 16, 1105–1110 (1976).
Zheng, J., Valavanis, K., and Gauch, J., Object extraction using color information in computer vision,Internat. Conf. Automation, Robotics and Computer Vision, ICARCV '90, Singapore (1990).
Davis, L.S., A survey of edge detection techniques,Computer Graphics and Image Processing 4, (3), 248–270 (1975).
Pitas, I. and Venetsanopoulos, A.N.,Nonlinear Digital Filters, Kluwer Academic Pulishers, Dordrecht (1990).
Lee, J., Digital image smoothing and the sigma filter,Computer Vision, Graphics and Image Processing 24, 255–269 (1983).
Rosenfeld, A., Image analysis: Problems, progress and prospects, in M. Fischler and O. Firschein, (eds),Computer Vision, Morgan Kaufmann, pp. 3–12 (1987).
Tukey, J.W.,Exploratory Data Analysis, Addison-Wesley, Reading, MA (1971).
Faugeras, O.D.,Fundamentals in Computer Vision, Cambridge University Press (1983).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Zheng, J., Valavanis, K.P. & Gauch, J.M. Noise removal from color images. J Intell Robot Syst 7, 257–285 (1993). https://doi.org/10.1007/BF01257768
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF01257768