Gray Image Contrast Enhancement by Optimal Fuzzy Transformation
The brief analysis of methods for contrast enhancement of gray images is performed. The application of fuzzy logic for image binarization and contrast enhancement is emphasized. The drawbacks of known methods are shown. To transfer from spatial domain to fuzzy one by the way of additional optimization of the of S-type membership function shape over its steepness by the change of order, which can be both whole number and fractional one, is proposed. The new method of image reconstruction from the smoothed one after the local contrast enhancement in the fuzzy domain is applied. The effectiveness of proposed method is illustrated on the examples.
KeywordsMembership Function Fuzzy Logic Contrast Enhancement Image Enhancement Fuzzy Membership Function
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- 3.Choi, Y.S., Krishnapuram, R.: A robust approach to image enhancement based on fuzzy logic. IEEE Trans. on Image Processing 6(10), 811–825 (1997)Google Scholar
- 4.Gonzales, R.C., Woods, R.E.: Digital Image Processing. Prantis Hall, Upper Saddle River (2002)Google Scholar
- 7.Sattar, F., Tay, D.B.H.: Enhancement of document images using multiresolution and fuzzy logic techniques. IEEE Signal Processing Letters 6(6), 811–825 (1999)Google Scholar
- 8.Tizhoosh, H.R.: Fuzzy image enhancement: an overview. In: Kerre, E., Nachtegal, M. (eds.) Fuzzy Techniques in Image Processing, Studies in Fuzziness and Soft Computing, pp. 137–171. Springer, Heidelberg (2000)Google Scholar
- 9.Tizhoosh, H.R., Michaelis, B.: Image enhancement based on fuzzy aggregation techniques. In: Proc. 16th Int. conference IEEE IMTC 1999, Venice, Italy, vol. 3, pp. 1813–1817 (1999)Google Scholar
- 10.Vorobel, R.A.: A method for image reconstruction with contrast improvement. Information Extraction and Processing 17(93), 122–126 (2002)Google Scholar
- 11.Vorobel, R., Datsko, O.: Image contrast improvement using change of membership function parameters. Bulletin of National University “Lvivska Politechnika”. Computer engineering and Information Technologies 433, 233–238 (2001)Google Scholar
- 13.Kacprzyk, J.: Fuzzy sets in system analysis (In Polish), PWN, Warsaw (1986)Google Scholar
- 14.Alsina, C., Trillas, E., Valverde, L.: Do we need Max, Min and 1-j in Fuzzy Sets Theory? In: Yager, R. (ed.) Fuzzy Sets and Possibility Theory, pp. 275–297. Pergamon, New York (1982)Google Scholar