IEEE Trans Image Process - Noise estimation from digital step-model signal.

Tópicos

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Resumo

This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as this paper is mostly dedicated to image processing, a 2D extension is proposed. The 2D performances for several noise distributions and noise models are presented and are compared with selected other methods.

Resumo Limpo

paper address nois estim digit domain propos nois estim base step signal model effici distribut nois reli smallest amplitud signal imag propos approach use polarizeddirect deriv nonlinear combin deriv estim nois distribut eg gaussian poisson speckl etc moment measur distribut can comput also calcul theoret basi nois distribut model d perform detail paper most dedic imag process d extens propos d perform sever nois distribut nois model present compar select method

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