Restricted guided filter with SURE-LET-based parameter optimization

摘要

) that delivers optimal results has not yet been reported, and the contrast of the filtered output is considerably reduced. In this paper, we present a restricted version of guided filtering that has better contrast-preserving characteristics, and use Stein's unbiased risk estimate (SURE) with an exhaustive search or a linear expansion of threshold (LET) to optimally tune the two above parameters. With SURE, the mean squared error (MSE) can be unbiasedly estimated without the requirement of the noise-free image. Experiments verified the accuracy of the SURE derivation and its effectiveness with respect to providing a better trade off between two interrelated objectives - noise reduction and edge-preservation.