Reliable Filters for Impulse Noise Suppression Methods Implementation and Experimental Analysis
Geeta Hanji1, M.V. Latte2
1Prof. Geeta Hanji, E & CE Department, P.D.A. Engg. College, Gulbarga ,India.
2Dr. M.V. Latte, JSS Institute for Technical Education, Bangalore, India.
Manuscript received on January 02, 2014. | Revised Manuscript received on January 04, 2014. | Manuscript published on January 05, 2014. | PP: 80-84 | Volume-4 Issue-6, January 2014. | Retrieval Number: F2474014615/2015©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Improving the quaity of the noisy digital images is an important concern and a fundamental problem in the field of image processing. For the noisy images, quality improvement via noise suppression (or denoising) can be achieved with linear and nonlinear filters. Nonlinear filters being the winners in the list of denoising filters are more concerned about preserving the edge and other fine details of an image and are popularly used in the field of image restoration applications. In this paper, a simple and effective approach to suppress salt and pepper impulse noise from highly noised digital image is reviewed and implemented. Better modifications are suggested and incorporated to enhance its denoising capability. The presented work is based on X-ray filtering scheme used in Videoclient3, one of popular image processing algorithms used in PITZ applications. X-ray filter in videoclient 3 compares the central (suspected to be noisy) pixel with neighbors to see if the central pixel needs replacement, and has a percentage to control how intensive the filtering process is. The estimation of the noisy pixels is obtained by local mean. The essential advantage of applying X-ray filter is to effectively suppress the heavy noise and preserve sharp details of the original image. The simulation results on standard test images demonstrate the filter’s simplicity and better denoising capability compared to state of art filters.
Keywords: X-ray filter, Videoclient3, PITZ applications, noise suppression.