Abstract
Radial basis functions are used in many fields of mathematics and image analysis. In this paper, we have used linear RBF, cubic RBF, multi-quadratic RBF, inverse multi-quadratic RBF and Gaussian RBF for the reconstruction of blurred images. Simulations and mathematical comparisons show that Gaussian RBF gives better result with respect to the other RBF methods for images reconstruction in artificial neural network.
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The authors are so grateful to the anonymous referee for a careful checking of the details and for helpful comments and suggestions that improve this paper.
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Paul, A., Bhattacharya, P., Biswas, P., Maity, S.P. (2015). Comparative Analysis of Image Deblurring with Radial Basis Functions in Artificial Neural Network. In: Sethi, I. (eds) Computational Vision and Robotics. Advances in Intelligent Systems and Computing, vol 332. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2196-8_16
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DOI: https://doi.org/10.1007/978-81-322-2196-8_16
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