Abstract
Image sharpening refers to any enhancement technique that highlights edges and fine details in an image. The conventional methods for sharpening the images has several drawbacks such as, complex and slow calculations, color loss, anisotropy effects etc. In this paper, a new fuzzy filter is proposed for sharpening the color images. The sharpening fuzzy filter consists of two sub-filters. The first sub-filter computes fuzzy distances between the central pixel and its neighbourhood for each color component. These distances determine the edge information present at each pixel. The purpose of the second sub-filter is to apply a sharpening parameter λ and a correction term ε to each pixel neighbourhood (3×3 window) thereby enhancing the edge information to get the sharpened image. The performance of the filter has been tested on various standard images and comparison is done both visually and quantitatively with other conventional sharpening filters.
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References
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., pp. 147–163. Pearson Education, London (2002)
Jain, A.K.: Fundamentals of Digital Image Processing, pp. 233–356. Prentice Hall, Pearson Education (1989)
Arce, G.R., Paredes, J.L., Mullan, J.: Nonlinear Filtering for Image Enhancement. In: Handbook of Image and Video Processing, pp. 81–100. Academic Press, London (2006)
Pal, S.K., King, R.A.: Image enhancement using smoothing with fuzzy sets. IEEE Trans. SMC-11(7), 494–501 (1981)
Russo, F., Ramponi, G.: Working on image data using fuzzy rules. In: Proc. Sixth European Signal Processing Conf. EUSIPCO 1992, August 24-27 (1992)
Russo, F., Ramponi, G.: Fuzzy operator for sharpening of noisy images. Electronics Letters 28(18), 1715–1717 (1992)
Wu-Fan, C., et al.: Wavelet analysis and its applications in image processing. Science Press Hall, Beijing (2002)
Fu, S.: Fuzzy bidirectional flow for adaptive image sharpening. In: IEEE International Conference on Image Processing (ICIP 2005), September 2005, pp. 917–920 (2005)
Schulte, S., Witte, V.D., Kerre, E.E.: Fuzzy noise reduction method for color images. IEEE Transaction on Image Processing 16(5), 1425–1436 (2007)
Schulte, S., et al.: Fuzzy Two-Step Filter for Impulse Noise Reduction From Color Images. IEEE Transaction on Image Processing 15(11), 3568–3579 (2006)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst., Man, Cybern. SMC-15(1), 116–132 (1985)
Chen, Z.Y., Abidi, B.R., Page, D.L., Abidi, M.A.: Gray-Level Grouping (GLG): An Automatic Method for Optimized Image Contrast Enhancement – Part I: The Basic Method. IEEE Transactions on Image Processing 15(8), 2290–2302 (2006)
Krotkov, E.P.: Active Computer Vision by Cooperative Focus and Stereo. Springer, New York (1989)
Buerkle, A., Schmoeckel, F., Kiefer, M., Amavasai, B.P., Caparrelli, F., Selvan, A.N., Travis, J.R.: Vision-based closed-loop control of mobile microrobots for micro handling tasks. In: Proc. SPIE. Microrobotics and Microassembly III, vol. 4568, pp. 187–198 (2001)
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Wilscy, M., Nair, M.S. (2008). A New Method for Sharpening Color Images Using Fuzzy Approach. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_7
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DOI: https://doi.org/10.1007/978-3-540-69812-8_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69811-1
Online ISBN: 978-3-540-69812-8
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