Efficient fixed-valued and random-valued impulse detection for accurate image restoration

This paper proposes a novel impulse detection method for the restoration of images corrupted by impulse noise. Conventional impulse detection methods tend to work well for fixed-valued impulse noise but poorly for random-valued impulse noise. The proposed method can accurately detect not only fixed-valued but also random-valued impulse noise by using two different systems. The first system detects impulse noise by considering the differences between the intensity of a target pixel and the output of a median filter. The second system verifies whether the impulse detection results obtained by the first system are correct. By using these systems, the proposed method can accurately detect both types of impulse noise even in highly corrupted images. Furthermore, the proposed method can be effectively used as a preprocessor for noise reduction filtering. Experiments are presented to demonstrate the effectiveness of the proposed method.