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Approximation Studies Using Fuzzy Logic in Image Denoising Process

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Control, Computation and Information Systems (ICLICC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 140))

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Abstract

In this work Lossy methods are used for the approximation studies, since it is suitable for natural images such as photographs. When comparing the compression codecs, it used as an approximation to human perception of reconstruction quality. In numerical analysis and approximation theory, basis functions are also called blending functions, because of their use in interpolation. Fuzzy Logic Systems are blending functions and it has been used to develop a Modified Fuzzy Basis Function (MFBF) and also its approximation capability has been proved. An iterative formula (Lagrange Equation) for the fuzzy optimization has been adopted in this paper. This formula closely relates with the membership function in the RGB colour space. By maximizing the weight in the objective function the noise in the image reduced, so that the filtered image approximates the original image.

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© 2011 Springer-Verlag Berlin Heidelberg

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Gopalan, S., Nair, M.S., Sebastian, S., Sheela, C. (2011). Approximation Studies Using Fuzzy Logic in Image Denoising Process. In: Balasubramaniam, P. (eds) Control, Computation and Information Systems. ICLICC 2011. Communications in Computer and Information Science, vol 140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19263-0_14

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  • DOI: https://doi.org/10.1007/978-3-642-19263-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19262-3

  • Online ISBN: 978-3-642-19263-0

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