International Journal of System & Software Engineering

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A Novel Image Restoration Algorithm Using NSCT and Pixel Level Fusion


Affiliations
1 Dept. of CS, College of Computer Science & Information Systems, Jazan University, Saudi Arabia
2 Dept. of ECE, RVS College of Engineering and Technology, Coimbatore, Tamil Nadu, India
     

   Subscribe/Renew Journal


This paper aims at providing an image enhancement algorithm for digital images especially corrupted by various noises. Image restoration is a technique used to construct a composite image containing mutual and significant information from noisy source image. The novelty of this paper is implemented via applying contourlet transform as well as directional filter bank. The source image is decomposed into base and detail layers, firstly. Then, the detail layer is further decomposed by DFT filter banks to pass away noises. The denoisy detail layer is appended to the base layer of the corresponding source image to obtain noise-free source images. Finally, all the noise-free source images are fused using average fusion rule. Resulted images using our algorithm are compared with state of the art denoisy methods to show the effectiveness of the proposed method. Our proposed method outperforms the state of the art fusion method.

Keywords

Decomposition, Denoisy, DFT, Noise, NSCT.
Subscription Login to verify subscription
User
Notifications
Font Size


  • A. L. da Cunha, J. P. Zhou, and M. N. Do, “The non-subsampled contourlet transform: Theory, design, and applications,” IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3089-3101, 2006.

  • A. L. da Cunha, J. P. Zhou, and M. N. Do, “Nonsubsampled contourlet transform: Filter design and application in denoising,” In IEEE International Conference on Image Processing, Genoa, Italy, pp. 749-752, 11-14 September 2005.

  • J. P. Zhou, A. L. da Cunha, and M. N. Do, “Nonsubsampled contourlet transform: Construction and application in enhancement,” In IEEE International Conference on Image Processing, Genoa, Italy, pp. 469-476, 11-14 September, 2005.

  • J. Dongxiao, and G. Yurong, “Underwater image de-noising algorithm based on nonsubsampled contourlet transform and total variation,” American Journal of Engineering and Technology Research, vol. 11, no. 12, 2011.

  • E. Candes, L. Demanet, D. Donoho, and L. Ying, Applied and Computational Mathematics, Department of Stanford University, Stanford, pp. 1-44, March 2006.

  • D. Barash, “A fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 6, pp. 844-847, June 2002.

  • A. Wong, “Adaptive bilateral filtering of image signals using local phase characteristics,” Signal Processing, vol. 88, no. 6, pp. 1615-1619, June 2008.

  • N. C. Gallagher, Jr. and G. L. Wise, “A theoretical analysis of the properties of median filters,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 29, pp. 1136-1141, 1981.

  • C. Tomasi, and R. Manduchi, “Bilateral filtering for gray and color images,” Proceedings of the 1998 IEEE International Conference on Computer Vision, pp. 836-846, Bombay, India, 1998.

  • E. Oho, N. Baba, M. Katoh, T. Nagatani, M. Osumi, K. Amako, and K. Kanaya, “Application of the Laplacian filter to high-resolution enhancement of SEM images,” Journal of Electron Microscopy Technique, vol. 1, no. 4, pp. 331-340, February 2005.

  • E. J. Candes, and D. Donoho, “Curvelet: A surprisingly effective nonadaptive representation for object with edges,” Proceeding of Curves and Surfaces IV, France, pp. 105-121, 1999.

  • E. J. Candes, L. Demanet, and D. L. Donoho, “Fast discrete curvelet transforms,” Applied and Computational Mathematics, California Institute of Technology, pp. 1-43, 2005.

  • J. Tao, and Z. Xin, “Research and application of image denoising method based on curvelet transform,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37, Part B2, Beijing 2008.


Abstract Views: 257

PDF Views: 6




  • A Novel Image Restoration Algorithm Using NSCT and Pixel Level Fusion

Abstract Views: 257  |  PDF Views: 6

Authors

M. Shanmugasundaram
Dept. of CS, College of Computer Science & Information Systems, Jazan University, Saudi Arabia
N. Shanmuga Vadivu
Dept. of ECE, RVS College of Engineering and Technology, Coimbatore, Tamil Nadu, India

Abstract


This paper aims at providing an image enhancement algorithm for digital images especially corrupted by various noises. Image restoration is a technique used to construct a composite image containing mutual and significant information from noisy source image. The novelty of this paper is implemented via applying contourlet transform as well as directional filter bank. The source image is decomposed into base and detail layers, firstly. Then, the detail layer is further decomposed by DFT filter banks to pass away noises. The denoisy detail layer is appended to the base layer of the corresponding source image to obtain noise-free source images. Finally, all the noise-free source images are fused using average fusion rule. Resulted images using our algorithm are compared with state of the art denoisy methods to show the effectiveness of the proposed method. Our proposed method outperforms the state of the art fusion method.

Keywords


Decomposition, Denoisy, DFT, Noise, NSCT.

References