A switching bilateral filter for images with edge preservation properties

In this paper, we propose a Switching Bilateral Filter for universal noise removal. The algorithm contains two stages: detection followed by filtering. We propose a new scheme called as Quadrant Median Vector, which contains important features like edges and fine details. The Quadrant Median Vector is utilized to allocate a Reference Median which is in turn compared with a current pixel to classify it as impulse noise, Gaussian noise, or noise-free. The proposed switching bilateral filter removes both Gaussian and impulse noise without using additional weighting function. The range filter inside the bilateral filter switches between the Gaussian and impulse modes depending on the noise classification result. Simulation results show that our noise detector has a high noise detection rate as well as a high classification rate for salt-and-pepper, uniform impulse noise and mixed impulse noise. In addition, the computational complexity of SBF is significantly less than that of other mixed noise filters.