PERFORMANCE ANALYSIS OF VARIOUS LYMPHOCYTES IMAGES DE-NOISING FILTERS OVER A MICROSCOPIC BLOOD SMEAR IMAGE

Abstract

Image Enhancement is the first and foremost step that has to be done in all image processing applications. It is used to improve the quality of digital images. Microscopic images are prone to addition of noise from various sources such as error in camera calibration, excess staining of microscopic slides, etc.; Image de-noising is an enhancement technique that is used to remove noise present in an image. Reducing noise of image and preserve the edges are always critical and challenging in image processing. In this paper we made an attempt to undertake the study of four types of noise (Salt-and-pepper, Gaussian noise, Speckle Noise and Poisson Noise) induced in a peripheral blood smear image and their removal using four types of spatial filters (Mean Filter, Median Filter, Gaussian filter and Wiener Filter), in order to judge the efficiency of various filters over different kind of noise.  For estimation of parametric values we can use Mean Square Error (MSE),  Normalized Absolute Error (NAE) and Normalized correlation (NK), Peak Signal to Noise Ratio (PSNR) and it has been shown that Weiner filter is an optimum filter for microscopic images.