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Image Denoising Using Earth Mover's Distance and Local Histograms
Nezamoddin N. Kachoui
Pages - 66 - 76     |    Revised - 25-02-2010     |    Published - 31-03-2010
Volume - 4   Issue - 1    |    Publication Date - March 2010  Table of Contents
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KEYWORDS
Denoising, Bilateral filtering, Local histogram, Earth mover’s distance.
ABSTRACT
In this paper an adaptive range and domain filtering is presented. In the proposed method local histograms are computed to tune the range and domain extensions of bilateral filter. Noise histogram is estimated to measure the noise level at each pixel in the noisy image. The extensions of range and domain filters are determined based on pixel noise level. Experimental results show that the proposed method effectively removes the noise while preserves the details. The proposed method performs better than bilateral filter and restored test images have higher PSNR than those obtained by applying popular Bayesshrink wavelet denoising method.
CITED BY (1)  
1 Selvi, M. (2014). EBMBDT: Effective Block Matching Based Denoising Technique using Dual Tree Complex Wavelet Transform. Machine Graphics and Vision, 23, 23-41.
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1 P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion”, IEEE Tran. on PAMI, 12(7), pp. 629-639, 1990.
2 G. Sapiro and D. L. Ringach, “Anisotropic diffusion of color images”, in Proc. Society of Photo- Optical Instrumentation Engineers (SPIE) Conference, 2657, pp. 471-482, 1996.
3 M. Ceccarelli, V. D. Simone, and A. Murli, “Well-posed anisotropic diffusion for image denois- Ing”, IEE Proc. on VISP, 149(4), pp. 244-252, 2002.
4 C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images”, in Proceedings of Intl Conference on Computer Vision (ICCV), pp. 836-846, 1998.
5 J. Xie and P. A. Heng, “Color image diffusion using adaptive bilateral filter”, in 27th Annual EMBS International Conference, pp. 3433-3436, 2005.
6 B. Zhang and J. P. Allebach, “Adaptive bilateral filter for sharpness enhancement and noise Removal”, IEEE Tran. on Image Processing, 17(5), pp. 664-678, 2008.
7 S. Paris and F. Durand, “A fast approximation of the bilateral filter using a signal processing Approach”, MIT technical report, MIT-CSAIL-TR-2006-073, 2006.
8 M. Elad, “On the bilateral filter and ways to improve it”, IEEE Tran. on Image Processing, 10(11), pp. 1141-1151, 2002.
9 D. L. Donoho and I. M. Johnstone, “Ideal spatial adaptation via wavelet shrinkage”, Biometrika, 81(1), pp. 425-455, Sept 1994.
10 S. G. Chang, B. Yu, and M. Vetterli, “Adaptive wavelet thresholding for image denoising and Compression”, IEEE Tran. on Image Processing, 9(9), pp. 1532-1546, 2000.
11 S. G. Chang, B. Yu, and M. Vetterli, “Spatially adaptive wavelet thresholding with context modeling for image designing”, IEEE Tran. on Image Processing, 9(9), pp. 1522-1531, 2000.
12 M. N. Do and M. Vetterli, “The finite ridgelet transform for image representation”, IEEE Transactions on Image Processing, 12(1), pp. 16-28, 2003.
13 S. Peleg, M. Werman, and H. Rom, “A unified approach to the change of resolution: Space and gray-level”, IEEE Tran. on PAMI, 11(7), pp. 739-742, 1989.
Dr. Nezamoddin N. Kachoui
Department of Systems Design Engineering, University of Waterloo , Waterloo, ON, Canada Present Affiliation: Harvard - MIT Healt h Sciences and Technology Harvard Medical School,Cambridge,MA,USA - United States of America