A new adaptive bilateral filtering

In the existing bilateral filtering algorithm, the domain parameters and range parameters need to be predefined. Parameters of a bilateral filter are fixed and cannot guarantee to be optimal. A new adaptive bilateral filtering (ABF) is proposed in this paper. The ABF obtains the domain parameters by estimating the local object scale to minimize edge blurring. The range parameters are set adaptively according to noise variance estimated in smooth areas of a sub image. The method can improve the filtering performance. To filter out strong noise, the value of domain parameters is increased. ABF avoids setting parameters solely by experience, and the domain parameters are set adaptively according to the local image features. ABF can improve the noise filtering ability and reserves edges. Experiments show that the adaptive bilateral filter is superior to traditional bilateral filters, anisotropic diffusion filters, and modified bilateral filters in both subjective and objective evaluations.