Abstract
This paper proposes a denoising model hybridized using wavelet and bilateral filters with fuzzy soft thresholding. The parameters of the proposed model are optimized with floating point genetic algorithm (FPGA). The model optimized with one image is used as a general denoising model for other images like Lena, Fetus, Ultrasound, Xray, Baboon, and Zelda. The performance of the proposed model is evaluated in denoising images injected with noises in different degrees; moderate, high and very high, and the results obtained are compared with those obtained with similar hybrid model with wavelet soft thresholding. Results demonstrate that the performance of the proposed model in terms of PSNR and IQI in denoising most of the images is far better than those with similar model with wavelet soft thresholding. It has also been observed that the hybrid model with wavelet soft thresholding fails to denoise images with very high degree of noises while the proposed model can still be capable of denoising.
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References
Albert, C.T., Moore, J.R., Glaser, S.D.: Wavelet Denoising Techniques with Applications to Experimental Geophysical Data. Signal Processing 89(2), 144–160 (2009)
Shui, P.-l., Zhao, Y.-B.: Image Denoising Algorithm using Doubly Local Wiener Filtering with Block-adaptive Windows in Wavelet Domain. Signal Processing 87(7), 1721–1734 (2007)
Donoho, D.L., Johnstone, I.M.: Ideal spatial adaptation by wavelet shrinkage. Biometrika 81(3), 425–455 (1994)
Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Analysis and Machine Intelligence 12(7), 629–639 (1990)
Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proc. Int. Conf. Computer Vision, pp. 839–846 (1998)
Rudin, L.I., Osher, S., Fatemi, E.: Onlinear total variation based noise removal algorithms. Physica D 60(1-4), 259–268 (1992)
Buades, Coll, B., Morel, J.: Neighborhood filters and PDE’s. Numerische Mathematik 105(1), 1–34 (2006)
Donoho, D.L.: De-noising by soft thresholding. IEEE Trans. on Inform. Theory 41(3), 613–627 (1995)
Donoho, D.L., Johnstone, I.M.: Adapting to unknown smoothness via wavelet shrinkage. Journal of the American Statistical Association 90(432), 1200–1224 (1995)
Donoho, D.L., Johnstone, I.M., Kerkyacharian, G., Picard, D.: Wavelet shrinkage: Asymptopia. Journal of Royal Statistics Society, Series B 57(2), 301–369 (1995)
Chang, S.G., et al.: Adaptive wavelet thresholding for image denoising and compression. IEEE Transactions on Image Processing 9, 1532–1546 (2000)
Chang, S.G., Yu, B., Vetterli, M.: Spatially adaptive wavelet thresholding with context modeling for image denoising. In: Proc. ICIP, pp. 535–539 (1998)
Tomasi, C., Manduchi, R.: Lateral filtering for gray and color images. In: Proc. Int. Conf. Computer Vision, pp. 839–846 (1998)
Zhang, M., Gunturk, B.: A New Image Denoising Method based on the Bilateral Filter. In: ICASSP, pp. 929–932. IEEE, Los Alamitos (2008)
Roy, S., Sinha, N., Sen, A.K.: Performance Analysis of Wavelet and Bilateral Filter based Denoising Models: Optimized by Genetic Algorithm. In: Proceedings of International Conference on Computing and Systems (ICCS) – 2010, pp. 257–262 (2010)
Mendel, J.M.: Fuzzy logic systems for engineering: a tutorial. Proceedings of IEEE 83(3), 345–377 (1995)
Roy, S., Sen, A.K., Sinha, N.: VQ-DCT based Image Compression: A New Hybrid Approach. Assam University Journal of Science and Technology 5(II), 73–80 (2010)
Wang, Z., Bovik, A.C.: A Universal Image Quality Index. IEEE Signal Processing Letters 9(3) (2002)
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Roy, S., Sinha, N., Sen, A.K. (2011). Fuzzy Soft Thresholding Based Hybrid Denoising Model. In: Nagamalai, D., Renault, E., Dhanuskodi, M. (eds) Advances in Digital Image Processing and Information Technology. DPPR 2011. Communications in Computer and Information Science, vol 205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24055-3_1
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DOI: https://doi.org/10.1007/978-3-642-24055-3_1
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