An Edge-Based Adaptive Method for Removing High-Density Impulsive Noise from an Image While Preserving Edges

ETRI Journal

关键词: median filter;    binarized image;    uniform region;    edge region;    Impulsive noise;   

Others  :  1186337
DOI  :  10.4218/etrij.12.0111.0392

【 摘 要 】

This paper presents an algorithm for removing high-density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line-weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image.

   

【 参考文献 】

• [1]F. Van der Heijden, Image Based Measurement System, Hoboken, NJ: John Wiley & Sons, Inc., 1994.
• [2]G. Giakos et al., “Noninvasive Imaging for the New Century,” IEEE Instrum. Meas. Mag., vol. 2, no. 2, June 1999, pp. 32-49.
• [3]I. Pitas, Digital Image Processing Algorithms and Applications, Hoboken, NJ: John Wiley & Sons, Inc., 2000.
• [4]R.C. Gonzalez and R.E. Woods, Digital Image Processing, 3rd ed., Upper Saddle River, NJ: Prentice Hall, 2008.
• [5]H. Ibrahim, N. Kong, and T. Ng; “Simple Adaptive Median Filter for the Removal of Impulse Noise from Highly Corrupted Images,” IEEE Trans. Consum. Electron., vol. 54, no. 4, Nov. 2008, pp. 1920-1927.
• [6]K. Srinivasan and D. Ebenezer, “A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noise,” IEEE Signal Process. Lett., vol. 14, no. 3, Mar. 2007, pp. 189-192.
• [7]Y. Dong and S. Xu, “A New Directional Weighted Median Filter for Removal of Random-Valued Impulse Noise,” IEEE Signal Process. Lett., vol. 14, no. 3, Mar. 2007, pp. 193-196.
• [8]B. Jeon, G. Chae, and C. Jeong, “ACWM Filter Design for Removing Impulsive Noise,” J. Korean Institute Inf. Scientists Engineers, Oct. 1997, pp. 142-145.
• [9]S. Zhang and M.A. Karim, “A New Impulse Detector for Switching Median Filters,” IEEE Signal Process. Lett., vol. 9, no. 11, Nov. 2002, pp. 360-363.
• [10]D. Brownrigg, “The Weighted Median Filter,” Commun. Assoc. Comput., Oct. 1984, pp. 807-818.
• [11]L.G. Shapiro and G.C. Stockman, Computer Vision, Prentence Hall, 2001, pp. 137-150.
• [12]R. Chan, C. Ho, and M. Nikolova, “Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail Preserving Regularization,” IEEE Trans. Image Process., vol. 14, no. 4, Oct. 2005, pp. 1479-1485.
• [13]H. Hwang and R. Haddad, “Adaptive Median Filters: New Algorithms and Results,” IEEE Trans. Image Process., vol. 14, no. 4, Apr. 1995, pp. 499-502.
• [14]Z. Wang and D. Zhang, “Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Image,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 46, no. 1, Jan. 1999, pp. 78-80.
• [15]W. Luo, “Efficient Removal of Impulse Noise from Digital Images,” IEEE Trans. Consum. Electron., vol. 52, no. 2, May 2006, pp. 523-527.
• [16]T. Chen and H.R. Wu “Adaptive Impulse Detection Using Center-Weighted Medina Filters,” IEEE Signal Process. Lett. vol. 8, no. 1, Jan. 2001, pp. 1-3.
• [17]N.I. Petrovic and V. Crnojevic, ”Universal Impulse Noise Filter Based on Genetic Programming,” IEEE Trans. Image Process., vol. 17, no. 7, July 2008, pp. 1109-1120.