Direction-based adaptive switching filter for removing high-density impulse noise

Abstract

A direction-based adaptive switching (DBAS) filter is presented for the removal of high-density impulse noise in images. The extrema detection and 28-directional detection are employed to discriminate the pixels as noisy or noise-free. If a pixel is classified as noisy, it will be replaced by a median or a mean value within an adaptive filter window with respect to different noise densities. Simulation results show that the miss-detection ratio and false-alarm ratio are both very low even at noise level as high as 90%. At the same time, better results are obtained in terms of the qualitative and quantitative measures. The peak signal-to-noise ratios increase by nearly 1 dB compared with other existing algorithms. In addition, the computation time is around 10 s for test images with resolutions of 512 × 512 since the proposed approach has low complexity.