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18 January 2010 Estimating the noise influence on recovering reflectances
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The evaluation of the noise present in the image acquisition system and the influence of the noise is essential to image acquisition. However the mean square errors (MSE) is not divided into two terms, i.e., the noise independent MSE (MSEfree) and noise dependent MSE (MSEnoise) were not discussed separately before. The MSEfree depends on the spectral characteristics of a set of sensors, illuminations and reflectances of imaged objects and the MSEfree arises in the noise free case, however MSEnoise originates from the noise present image acquisition system. One of the authors (N.S.) already proposed a model to separate the MSE into the two factors and also proposed a model to estimate noise variance present in image acquisition systems. By the use of this model, we succeeded in the expression of the MSEnoise as a function of the noise variance and showed that the experimental results agreed fairly well with the expression when the Wiener estimation was used for the recovery. The present paper shows the extended expression for the influence of the system noise on the MSEnoise and the experimental results to show the trustworthiness of the expression for the regression model, Imai-Berns model and finite dimensional linear model.
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Mikiya Hironaga and Noriyuki Shimano "Estimating the noise influence on recovering reflectances", Proc. SPIE 7529, Image Quality and System Performance VII, 75290M (18 January 2010);

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