Stair Blue Noise Sampling

摘要

A common solution to reducing visible aliasing artifacts in imagernreconstruction is to employ sampling patterns with a blue noisernpower spectrum. These sampling patterns can prevent discerniblernartifacts by replacing them with incoherent noise. Here, we proposerna new family of blue noise distributions, Stair blue noise, which isrnmathematically tractable and enables parameter optimization to obtainrnthe optimal sampling distribution. Furthermore, for a givenrnsample budget, the proposed blue noise distribution achieves a significantlyrnlarger alias-free low-frequency region compared to existingrnapproaches, without introducing visible artifacts in the midfrequencies.rnWe also develop a new sample synthesis algorithm thatrnbenefits from the use of an unbiased spatial statistics estimator andrnefficient optimization strategies.