Noise gradient reduction based on morphological dual operators

Noise gradient is reduced while image details gradient is also reduced by a filter. For the image corrupted by impulse noise, a novel approach of noise gradient reduction is proposed based on a pair of morphological dual operators. The noise image is filtered by a pair of morphological dual operators respectively, and then the two filtered images are provided with the complementary characteristics of the noise gradient position. This feature results from the unsymmetric behaviour of the pair of morphological dual operators, and it can be applied to reduce the noise gradient effectively. This approach is presented in detail and the experimental results show that the approach not only reduces noise gradient effectively, but also maintains image details gradient. Compared with the classical morphological dual operators, the generalised morphology dual operators have smaller root mean square error on the premise of the close computation and time.