Comparison of Denoising Filters on Greyscale TEM Image for Different Noise
Garima Goyal · IOSR Journal of Computer Engineering · 2012
TEM (Transmission Electron Microscopy) are currently the most widely used techniques to study nanoparticles morphology.Removal of noise from an image is one of the most important tasks in image processing.Depending on the nature of the noise, such as additive or multiplicative type of noise, there are several approaches towards removing noise from an image.Image De-noising improves the quality of images acquired by optical, electro-optical or electronic microscopy.This paper compares five filters on the measures of mean of image, signal to noise ratio, peak signal to noise ratio & mean square error.In this work four types of noise (Gaussian noise, Salt & Pepper noise, Speckle noise and Poisson noise) is used and image de-noising performed for different noise.Further results have been compared for all noises. .In this paper four types of noise are used and image de-noising performed for different noise by various filters (WFDWT, BF, HMDF, FDE, and DVROFT).Further results have been compared for all noises.It is observed that for Gaussian Noise WFDWT & for other noises HMDF has shown the better performance results.