Variance Stabilization for Noisy+Estimate Combination in Iterative Poisson Denoising
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Sivut | 1086-1090 |
| Sivumäärä | 5 |
| Julkaisu | IEEE Signal Processing Letters |
| Vuosikerta | 23 |
| Numero | 8 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 1 elokuuta 2016 |
| OKM-julkaisutyyppi | A1 Alkuperäisartikkeli |
Tiivistelmä
We denoise Poisson images with an iterative algorithm that progressively improves the effectiveness of variance-stabilizing transformations (VST) for Gaussian denoising filters. At each iteration, a combination of the Poisson observations with the denoised estimate from the previous iteration is treated as scaled Poisson data and filtered through a VST scheme. Due to the slight mismatch between a true scaled Poisson distribution and this combination, a special exact unbiased inverse is designed. We present an implementation of this approach based on the BM3D Gaussian denoising filter. With a computational cost at worst twice that of the noniterative scheme, the proposed algorithm provides significantly better quality, particularly at low signal-to-noise ratio, outperforming much costlier state-of-the-art alternatives.