A novel quadratic type variational method for efficient salt-and-pepper noise removal

Salt-and-pepper impulse noise is one commonly encountered noise type during image and video communication. So far the state of the art methods can reasonably restore images corrupted by salt-and-pepper noise whose level is up to 90%. We propose a novel quadratic type variational formulation of this noise removal problem. This approach first uses a simple yet fast method to eliminate all salt-and-pepper noise pixels as well as possibly some clean pixels, then the clean image is efficiently reconstructed from the remaining clean pixels by minimizing a carefully designed functional. Because the functional is quadratic type, fast unconditional convergence is guaranteed. Simulation results show that the proposed method outperforms previously published results and can tolerate noise level of as much as 95%.