Abstract
In general, it is known that an adaptive filter adjusts its parameters iteratively such as size of the working window, decision threshold values used in two stage detection-estimation based switching filters, number of iterations etc. It is also known that nonlinear filters such as median filters and its several variants are popularly known for their ability in dealing with the unknown circumstances. In this paper an efficient and simple adaptive nonlinear filtering scheme is presented to eliminate the impulse noise from the digital images with an impulsive noise detection and reduction scheme based on adaptive nonlinear filter techniques. The proposed scheme employs image statistics based dynamically varying working window and an adaptive threshold for noise detection with a Noise Exclusive Median (NEM) based restoration. The intensity value of the Noise Exclusive Median (NEM) is derived from the processed pixels in local neighborhood of a dynamically adaptive window. In the proposed scheme use of an adaptive threshold value derived from the noisy image statistics returns more precise results for the noisy pixel detection. The proposed scheme is simple and can be implemented as either a single pass or a multi-pass with a maximum of three iterations with a simple stopping criterion. The goodness of the proposed scheme is evaluated with respect to the qualitative and quantitative measures obtained by MATLAB simulations with standard images added with impulsive noise of varying densities. From the comparative analysis it is evident that the proposed scheme out performs the state-of-art schemes, preferably in cases of high-density impulse noise.
Highlights
One of the challenges researchers in the field of image processing facing today is noise suppression from the images with detail preservation such as edges
Adaptive 2-stage novel algorithm (NAF) proposed in this paper is a detection-estimation based approach in which the novel adaptive threshold based noise detection is followed by the application of NEMF scheme only to the corrupted pixels
Performance of the proposed Novel Median Filter (NAF) scheme is validated with the MATLAB simulation performed on synthetic images like Cameraman, Lena etc
Summary
One of the challenges researchers in the field of image processing facing today is noise suppression from the images with detail preservation such as edges. At low noise densities performance of TSMF is good, but conditions of higher noise densities yield poor performance Another novel filter with a three-level hierarchical soft-switching noise detection process is suggested in a noise adaptive soft switching median (NASSMF) filter [8].Based on the fuzzy set concept, pixels are classified in to uncorrupted pixel, isolated impulse noise, non-isolated impulse noise or image object’s edge pixel. Fast and efficient decision-based algorithm [11] is proposed to overcome the above stated problem Results obtained with this filter present better visual appearance for impulse noise corrupted images with good edge preservation capability. In general we can conclude saying that the conditions of higher noise densities require working window of larger size for better noise removal which results in less correlation between noise affected pixel values and adaptive thresholds (derived based on the image statistics) in decision making in two stage detection-estimation based filters. Decision strategy is framed as below : Declare the reference (or test) pixel P(i,j) as noisy iff its luminance value is either a ‘0’ or ‘255’ and if it has ‘W’ or more number of non-noisy pixels where W ≥ T/3, with T=Total number of pixels in the working window
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