  This paper proposes a new technique based on nonlinear Adaptive Median filter
(AMF) for image restoration. Image denoising is a common procedure in digital
image processing aiming at the removal of noise, which may corrupt an image
during its acquisition or transmission, while retaining its quality. This
procedure is traditionally performed in the spatial or frequency domain by
filtering. The aim of image enhancement is to reconstruct the true image from
the corrupted image. The process of image acquisition frequently leads to
degradation and the quality of the digitized image becomes inferior to the
original image. Filtering is a technique for enhancing the image. Linear filter
is the filtering in which the value of an output pixel is a linear combination
of neighborhood values, which can produce blur in the image. Thus a variety of
smoothing techniques have been developed that are non linear. Median filter is
the one of the most popular non-linear filter. When considering a small
neighborhood it is highly efficient but for large window and in case of high
noise it gives rise to more blurring to image. The Centre Weighted Median (CWM)
filter has got a better average performance over the median filter [8]. However
the original pixel corrupted and noise reduction is substantial under high
noise condition. Hence this technique has also blurring affect on the image. To
illustrate the superiority of the proposed approach by overcoming the existing
problem, the proposed new scheme (AMF) Adaptive Median Filter has been
simulated along with the standard ones and various performance measures have
been compared.
