Design and Development of an Improved Adaptive Median Filtering Method for Impulse Noise Detection

A Study on Image Restoration Algorithm in Random-Valued Impulse Noise Environment

“…The gray dot is the center pixel ) , ( j i X and black dots are the two pixels to be used in following calculating. In each sub window, the sum of absolute value of difference between ) , ( j i X and the other pixel is denoted as 1 v…”

“…Standard median (SM) filter has been widely used in removing random-valued impulse noise, where the output pixel is set to the median of the neighborhood pixels [1]. However, the standard median filter tends to modify not only noise pixels but also noise-free pixels.…”

“…SM filter is the most important and popular nonlinear filter which exploits the rank-order information of pixel intensities within a filtering window and replaces the center pixel with the median value [1]. Mask size can be defined as (1).…”

Mean of Median Absolute Derivation Technique for Speckle Noise Variance Estimation in Computerised Tomography Images

“…The value of noise variance obtained during estimation determines the extent to which the adaptive filter is tuned to achieve good noise suppression. Adaptive filters use the estimated noise variance as an input to determine the extent to vary filter centre-pixel weight or the window size to ensure better noise suppression [2,3]. The priori knowledge of the type of noise present in a noisy image helps in the accuracy of the estimation [5].…”

“…The logarithmic transformation is applied to speckle noise so that linear filtering is used to suppress noise in the noisy image. When a noisy image is filtered using linear filter, the expression for the logarithm of approximate speckle noise approximate image edge and residual image surface is computed using (3) where h(m,n) is the linear filter kernel. …”