The week's pick
Random Articles
Reseach Article
Impulse Denoising Algorithm for Gray and RGB Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 70 - Number 2 |
| Year of Publication: 2013 |
| Authors: A. Rajamani, V. Krishnaveni |
10.5120/11932-7716
|
A. Rajamani, V. Krishnaveni . Impulse Denoising Algorithm for Gray and RGB Images. International Journal of Computer Applications. 70, 2 ( May 2013), 4-9. DOI=10.5120/11932-7716
Abstract
Noise removal plays vital role in image processing and also important pre processing task before performing post operation like Image segmentation etc. . This paper presents a effective and efficient algorithm in order to remove impulse noise from gray scale and color images. Challenging results show the superior performance of the proposed filtering algorithm compared to the other standard algorithms such as Standard Median Filter (SMF), Median Filter (MF), Weighted Median Filter (WMF) and Trimmed Median Filter (TMF). Furthermore, various performance metrics such as the MSE, PSNR and SSIM have been compared with Existing standard algorithms. The computational time for the denoised image is calculated for different noise levels and the proposed algorithm has lower computational time, hardware complexity and ease in operation. The obtained results prove that it has better qualitative analysis by improving visual appearance and challenging quantitative measures even at high noise densities ranging up to 90%.
References
- Rafael C. Gonzalez, Richard Eugene Woods, Steven L. Eddins . 2004. Digital image Processing. Pearson Education.
- Jayaraman,S. , Veerakumar,T. , and Esakkirajan,S. 2009. Digital Image Processing. Tata McGraw-Hill Education.
- Gallagher, N. C. ,Jr. and Wise,G. L. 1981. A Theoretical Analysis of the Properties of Median Filters. IEEE Trans. Acoust. , Speech and Signal Processing, 29, 1136-1141.
- Nodes,T. A,,Gallagher,N. C. 1987. Median Filters: Some Modifications and their properties. IEEE Trans. Acoust. , Speech and Signal Processing, 30, 739-746 .
- Astola,J. ,Kuosmanen. P. 1997. Fundamentals of Non-Linear Digital Filtering. BocRaton, CRC. Forman, G. 2003. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3 (Mar. 2003), 1289-1305.
- Yin,L. ,Gabbouj,M. , and Neuvo,Y. 1996. Weighted Median Filters: A Tutorial. IEEE Transactions on Circuit and and Systems - 11: Analog and Signal Processing, 4(3).
- Brownrig,D. R. 1986. Generation of Representative members of a Weighted median filter class. Proc. Inst. Elec. Eng. (133), 445-448.
- Chen, L. ,Chiueh,T. D and Hsiao,J. 1994. Design and VLSI Implementation of Real-Time Weighted Median Filters. Proc. 1994 Asia-Pacific Conference on Circuit and Systems, 91-96.
- Chan,R. H. ,Ho,C. W. , and Nikolova,M. 2005. Salt and pepper noise removal by median type noise detectors and detail reserving regularization. IEEE Transactions on Image Processing,14(10), 1479-1485.
- Buades. ,Coll, A. B. , and. Moral,J. M. 2005. A Review of image denoising algorithms with a new one. Multiscale model. simul. ,4(2), 490-530.
- Esakkirajan,S. ,Veerakumar,T. , Adabala Subramanyam, N. ,and PremChand,C. H. 2011. Removal of High Density Salt and Pepper Noise Through Modified Decision based. Unsymmetric Trimmed Median Filter. IEEE signal processing letters,18(5), 287-291
- Vijaykumar,V. R. ,Ebenezer,D. ,and Vanathi ,P. T. 2008. Detail preserving median based filter for impulse noise removal in digital images, IndiaICSP2008 Proceedings IEEE, 978-1-4244-2179-4.
- Fang et al. ,2004. Speckle Noise Reduction in SAR Imagery Using a Local Adaptive Median Filter", GIScience and Remote Sensing, 41(3), 244-266.
- Subhojit Sarker, Shalini Chowdhury, Samanwita Laha and Debika Dey. 2012. Use of non-local means filter to denoise image corrupted by salt and pepper noise,Signal & Image Processing : An International Journal", 3(2), DOI : 10. 5121/sipij. 2012. 3217 223.
Index Terms
Keywords