期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 17, 期 10, 页码 1737-1754出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2008.2001399
关键词
clipping; digital imaging sensors; noise estimation; noise modeling; overexposure; Poisson noise; raw-data
资金
- Finnish Funding Agency for Technology and Innovation (Tekes)
- AVIPA/AVIPA2
- Academy of Finland [213462]
We present a simple and usable noise model for the raw-data of digital imaging sensors. This signal-dependent noise model, which gives the pointwise standard-deviation of the noise as a function of the expectation of the pixel raw-data output, is composed of a Poissonian part, modeling the photon sensing, and Gaussian part, for the remaining stationary disturbances in the output data. We further explicitly take into account the clipping of the data (over- and under-exposure), faithfully reproducing the nonlinear response of the sensor. We propose an algorithm for the fully automatic estimation of the model parameters given a single noisy image. Experiments with synthetic images and with real raw-data from various sensors prove the practical applicability of the method and the accuracy of the proposed model.
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