Analysis of different filters for noise reduction in images

Reducing noise from images still prevails as a challenge in the field of image processing. Image processing proves to be very successful in allowing an extensive range of algorithms to be applied to the input data set in the form of image and retrieve crucial results. These algorithms tend to avoid problems such as noise and signal distortion. An image obtained after noise removal has higher clarity in terms of both interpretation and analysis for study in different fields such as medical, satellite imaging and radar. This paper attempts to analyze the efficacy of different filtering techniques on the image containing 04 types of noises Gaussian, Poisson, Salt & Pepper and Speckle. The performance of filtering techniques Median, Average and Wiener is evaluated by performance measuring parameters execution time and entropy.