A new impulse detection and filtering algorithm is proposed for restoration of images that are highly corrupted by impulse noise. It is based on the average absolute value of four convolutions obtained by one-dimensional Laplacian operators. The proposed algorithm can effectively remove the impulse noise with a wide range of noise density and produce better results in terms of the qualitative and quantitative measures of the images even at noise density as high as 90%. Extensive simulations show that the proposed algorithm provides better performance than many of the existing switching median filters in terms of noise suppression and detail preservation.
In this paper, a new nonlinear median based filtering technique is introduced for the enhancement of medical images that are highly contaminated by impulse noise. The proposed Detail Preserving Fast Median Filtering (DPFMF) technique is more effective in eliminating fixed value impulse noise and preserving the image details. The filter replaces a corrupted pixel by the median value of the fast median filter or by the value computed based on a unique criterion applied to the processed neighboring pixel values. The uncorrupted pixels are left undisturbed. Simulation studies show that the proposed filter can eliminate impulse noise of densities up to 80% while preserving the edges and fine details satisfactorily. The performance is evaluated by applying the proposed filter on different gray scale images and the superior results obtained in terms of subjective and objective evaluation are presented.
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