Double operator morphological filters

The traditional morphological filtering operators are time consuming and have poor alternative ability to suppress noise. Based on the structure elements of central complementary and alternating dual operators, double operator morphological filters are proposed in this paper. The filters inherit the important properties of the classic morphological filters, such as increasingness, duality and idempotence, but they lack the extensibility and anti-extensibility. With discrete neighborhood property, the double operator morphological filters can remove the block noise whose size is bigger than the structure elements by using the alternating small structure elements. And also they can suppress the noise while preserving the image details. Experimental results show that the double operator morphological filters have better noise suppression performance than the basic and popular morphological filters. Moreover, having the same filtering effect, the computation of the double operator morphological filters is smaller than others, and the final filtered image has a higher peak signal to noise ratio and a smaller root mean square error.