Analytical Comparison of Noise Reduction Filters for Image Restoration Using SNR Estimation
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : Poorna Banerjee Dasgupta|
|DOI : 10.14445/22312803/IJCTT-V17P123|
Poorna Banerjee Dasgupta. "Analytical Comparison of Noise Reduction Filters for Image Restoration Using SNR Estimation". International Journal of Computer Trends and Technology (IJCTT) V17(3):121-124, Nov 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Noise removal from images is a part of image restoration in which we try to reconstruct or recover an image that has been degraded by using a priori knowledge of the degradation phenomenon. Noises present in images can be of various types with their characteristic Probability Distribution Functions (PDF). Noise removal techniques depend on the kind of noise present in the image rather than on the image itself. This paper explores the effects of applying noise reduction filters having similar properties on noisy images with emphasis on Signal-to-Noise-Ratio (SNR) value estimation for comparing the results.
 Rafael C. Gonzalez ,Richard E. Woods. Digital Image Processing, 3rd Edition, Prentice Hall Publications, 2000.
 Peter Kellman, Elliot R. McVeigh. Image reconstruction in SNR units: A general method for SNR measurement. Wiley Publications, 2005.
 John C. Russ. The image processing handbook. 5th Edition CRC Press,2007.
 Suk Hwan Lim ; Maurer, R. ; Kisilev, P. “Denoising scheme for realistic digital photos from unknown sources”. IEEE International Conference on Acoustics, Speech and Signal Processing, 2009.
 D. J. Schroeder. Astronomical Optics ,2nd Edition, Academic Press, 1999.
 Tania Stathaki. Image fusion: algorithms and applications. Academic Press, 2008
Noise, Image filters, Probability Distribution Function (PDF), Signal-to-Noise-Ratio (SNR).