A detail preserving filter for impulse noise removal

It is known that digital images are frequently corrupted by impulse noise due to errors generated in camera sensors, analog-to-digital conversion and communication channels. Therefore, it is imperative to remove impulse noise in order to facilitate the subsequent processing such as edge detection, segmentation, analysis, and pattern recognition etc. Many linear and nonlinear filtering techniques have been proposed earlier to remove impulse noise, however these filter often bring along blurred and distorted image of details. Filtering an image to attenuate noise while keeping the image details preserved is one of the most important issues. In this paper a detail preserving filter for impulse noise removal is proposed, which is based on the soft-switching median (SWM) filter. In the first, the impulse noise candidates are detected by arranging the pixels in order in the sliding window. In the second, we analyze the noise candidates and classify them into noise-free pixels, noisy pixels and detail pixels (edges and smooth changing regions). Finally, the process employed the rank-ordered mean filter (ROM) to remove the corrupted pixels and the details can be restored and preserved. Extensive experiments indicate that the proposed method can effectively restore images corrupted with impulse noise and performs significantly better in terms of noise suppression and detail preservation than a number of existing nonlinear techniques.