IEEE Trans Image Process - A closed-form approximation of the exact unbiased inverse of the Anscombe variance-stabilizing transformation.

Tópicos

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Resumo

We presented an exact unbiased inverse of the Anscombe variance-stabilizing transformation in [M. M?kitalo and A. Foi, "Optimal inversion of the Anscombe transformation in low-count Poisson image denoising," IEEE Trans. Image Process., vol. 20, no. 1, pp. 99-109, Jan. 2011.] and showed that when applied to Poisson image denoising, the combination of variance stabilization and state-of-the-art Gaussian denoising algorithms is competitive with some of the best Poisson denoising algorithms. We also provided a MATLAB implementation of our method, where the exact unbiased inverse transformation appears in nonanalytical form. Here, we propose a closed-form approximation of the exact unbiased inverse in order to facilitate the use of this inverse. The proposed approximation produces results equivalent to those obtained with the accurate (nonanalytical) exact unbiased inverse, and thus, notably better than one would get with the asymptotically unbiased inverse transformation that is commonly used in applications.

Resumo Limpo

present exact unbias invers anscomb variancestabil transform m mkitalo foi optim invers anscomb transform lowcount poisson imag denois ieee tran imag process vol pp jan show appli poisson imag denois combin varianc stabil stateoftheart gaussian denois algorithm competit best poisson denois algorithm also provid matlab implement method exact unbias invers transform appear nonanalyt form propos closedform approxim exact unbias invers order facilit use invers propos approxim produc result equival obtain accur nonanalyt exact unbias invers thus notabl better one get asymptot unbias invers transform common use applic

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