Speckle Noise Removal and Edge Detection using Mathematical Morphology
Arpit Singhal1, Mandeep Singh2
1Arpit Singhal, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India.
2Mandeep Singh, Assistant Professor, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India.
Manuscript received on October 04, 2011. | Revised Manuscript received on October 21, 2011. | Manuscript published on November 05, 2011. | PP: 146-149 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0172091511/2011©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: Mathematical morphology is a new subject established based on rigorous mathematical theories. In the basis of set theory, mathematical morphology is used for image processing, analyzing and comprehending. It is a powerful tool in the geometric morphological analysis and description. Noise removal and edge detection are very important pre-processing steps. For removing speckle noise nonlinear filtering techniques are better then liner filtering techniques image processing applications, at removing noise without affecting thin and small image features. One structure for designing nonlinear filters is mathematical morphology. Also the need of edge detection is to find the discontinuities in depth, discontinuities in surface orientation, changes in material properties and variations in scene illumination. Again mathematical morphological operations are used for edge detection and enhancement .This paper describes removal of speckle noise presented in images and then to obtain the useful edges in the output image obtained after noise removed using mathematical morphology.
Keywords: Mathematical morphology, speckle noise, edge detection.