The week's pick
Random Articles
Reseach Article
Performance Analysis of Impulse Denoising Techniques in Magnetic Resonance Imaging
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 136 - Number 12 |
| Year of Publication: 2016 |
| Authors: Ram Paul Hathwal, Rajesh Kumar Gupta, Singara Singh Kasana |
10.5120/ijca2016908607
|
Ram Paul Hathwal, Rajesh Kumar Gupta, Singara Singh Kasana . Performance Analysis of Impulse Denoising Techniques in Magnetic Resonance Imaging. International Journal of Computer Applications. 136, 12 ( February 2016), 17-22. DOI=10.5120/ijca2016908607
Abstract
Medical images are corrupted by noise during their acquisition and transmission. Image denoising involves manipulation of the image data to produce a visually original quality image. The ultimate goal of medical image denoising technique is to compromise between the noise suppression and preservation of image details. The best possible information is required by the clinician for an accurate diagnosis. It has become an essential exercise especially in the Magnetic Resonance Imaging (MRI). In this work, we have taken magnetic resonance images infected with salt and pepper noise and have used three different de-noising techniques namely median filter, adaptive median filter, and a nonlinear cascade filter. All the three filters are used to reduce image noise at different densities and their Peak Signal to Noise Ratios (PSNR) are compared. This experimental analysis helps us increase the accuracy of MRI for easy diagnosis and determine which filter might be best suited for rectification of corrupted MRI.
References
- S. J. Ko and Y. H. Lee, “Center weighted median filters and their applications to image enhancement”, IEEE Transactions on Circuits and Systems, vol. 38, no. 9, pp. 984–993, 1991
- T. Sun and Y. Neuvo, “Detail-preserving median based filters in image processing”, Pattern Recognition Letters, vol. 15, no. 4, pp. 341–347, 1994.
- B. Jeong and Y. H. Lee, “Design of weighted order statistic filters using the perceptron algorithm,” IEEE Transaction Signal Processing, vol. 42, no. 11, pp. 3264–3269, 1994.
- A. Macovski, “Noise in MRI”, Magn. Reson. Medical, vol. 36, pp. 494–497, 1996.
- E. Abreu, M. Lightstone, S. K. Mitra, and K. Arakawa, “A new efficient approach for the removal of impulse noise from highly corrupted images”, IEEE Transactions Image Processing, vol. 5, no. 6, pp. 1012–1025, 1996.
- T. Chen, K. K. Ma, and L. H. Chen, “Tri-state median filter for image denoising”, IEEE Transactions on Image Processing, vol. 8, no. 12, pp. 1834–1838, 1999.
- A. Achim, A. Bezerianos, and P. Tsakalides, “Novel Bayesian multiscale method for noise removal in medical MRI images,” IEEE Transactions Medical Imaging, vol. 20, no. 8, pp. 772–783, 2001.
- H.-L. Eng and K.-K. Ma, “Noise adaptive soft-switching median filter,” IEEE Transactions on Image Processing, vol. 10, pp. 242–251, 2001.
- A. Samsonov and C. Johnson “Noise-Adaptive Nonlinear Diffusion Filtering of MR Images With Spatially Varying Noise Levels”, Magnetic Resonance in Medicine, vol. 52, pp. 798-806, 2004.
- R. H. Chan, C. W. Ho, and M. Nikolova, “Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization,” IEEE Transaction on Image Process., vol. 14, no. 10, pp. 1479–1485, 2005.
- A. Buades, B. Coll, and J. M. Morel, “A Review of Image Denoising Algorithms, with a new one”, Journal of Multiscale Modeling and Simulation, vol.4, no.2, pp. 490-530, 2005.
- W. Luo, “An efficient detail-preserving approach for removing impulse noise in images”, IEEE Sign al Process. Lett., vol. 13, no. 7, pp.413–416, 2006.
- T. C. Lin, P. T. Yu, “A new adaptive center weighted median filter for suppressing impulsive noise in images”, Information Sciences 177, pp. 1073–1087, 2007.
- D. Yiqiu, and S. Xu, “A New Directional Weighted Median Filter for Removal of Random-Valued Impulse Noise”, IEEE Signal Processing Letters, vol. 14, no. 3,pp. 193-196, 2007.
- S. Balasubramanian, S. Kalishwaran, R. Muthuraj, D. Ebenezer, V. Jayaraj , “ An Efficient Non-linear Cascade Filtering Algorithm for Removal of High Density Salt and Pepper Noise in Image and Video sequence”. International conference on “Control, Automation, Communication and Energy Conservation -2009”, 2009.
- L. Mitiche, “A review of wavelet denoising in MRI and ultrasound imaging,” Recent Advances in Intelligent Computational Systems(RAICS), vol. 20, no. 8, pp. 772–783, 2011.
Index Terms
Keywords