  Human Identity verification has always been an eye-catching goal in digital
based security system. Authentication or identification systems developed using
human characteristics such as face, finger print, hand geometry, iris, and
voice are denoted as biometric systems. Among the various characteristics, Iris
recognition trusts on the idiosyncratic human iris patterns to find out and
corroborate the identity of a person. The image is normally contemplated as a
gathering of information. Existence of noises in the input or processed image
effects degradation in the image superiority. It should be paramount to restore
original image from noises for attaining maximum amount of information from
corrupted images. Noisy images in biometric identification system cannot give
accurate identity. So Image related data or information tends to loss or
damage. Images are affected by various sorts of noises. This paper mainly
focuses on Salt and Pepper noise, Gaussian noise, Uniform noise, Speckle noise.
Different filtering techniques can be adapted for noise diminution to develop
the visual quality as well as understandability of images. In this paper, four
types of noises have been undertaken and applied on some images. The filtering
of these noises uses different types of filters like Mean, Median, Weiner,
Gaussian filter etc. A relative interpretation is performed using four
different categories of filter with finding the value of quality determined
parameters like mean square error (MSE), peak signal to noise ratio (PSNR),
average difference value (AD) and maximum difference value (MD).
