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An Implementation of the Median Filter and Its Effectiveness on Different Kinds of Images. Kevin Liu 2006-2007 Thomas Jefferson High School for Science and Technology. Abstract. Digital image filtering techniques Effectiveness of the median filter with different inputs.
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An Implementation of the Median Filter and Its Effectiveness on Different Kinds of Images Kevin Liu 2006-2007 Thomas Jefferson High School for Science and Technology
Abstract • Digital image filtering techniques • Effectiveness of the median filter with different inputs. • Scenery, objects, and people • Criteria: noise reduction and extent of blurring
Introduction and Background • Digital image processing first developed in the 1960's • Clear out noise or useless and distracting information in pictures • Missing pixels and wrong pixels • Inevitable when converting analog information into a digital form • transmission of image files from one location to another through physical mediums or through wireless communication.
Larger Purpose • Processing and enhancing digital images • The effectiveness of the median filter on different images • When to use the median filter • Blurring effects
Procedures and Methods • Varying intensity – size of window • Java – low number of Java classes • Noise introduction Module • Objects, people, scenery • Noise elimination quality • Extent of reduction in quality
Median Filter • Sliding window
Development • One module • 3 by 3 sliding window • Insertion Sort • Ignores edges • Noise introduction – percent probabibility
Sample Effects • Noise reduction • Noise reduction
Sample Effects • Blurring Effects
Sample Effects • Blurring Effects
Conclusions • Noise elimination equally effective • Reduction in quality most severe in scenery • Followed by people • Objects least affected