Description: 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 ua
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