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P.D. Pinto, J.M. M. Linhares, S.M. C. Nascimento, D.H. Foster, K. Amano; Detecting Natural Departures From Exponential Luminance Frequency Distributions in Natural Scenes . Invest. Ophthalmol. Vis. Sci. 2005;46(13):4574.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: The luminance frequency distribution in many rural scenes can be approximated by an exponential function (Pinto, 2004, MPhil Thesis, UMIST, UK). The purpose of this work was to investigate whether observers prefer images of scenes with their native luminance frequency distributions or with exactly exponential frequency distributions. Methods: Images of rural scenes were obtained with a hyperspectral imaging system (Foster et al., 2004, Visual Neurosci., 21, 331–336). Spectral–radiance functions at each pixel were estimated from gray reference surfaces located in the scene and from calibration data obtained with a telespectroradiometer. For each image, its luminance frequency distribution was then derived and a set of images with exactly exponential distributions but with different coefficients were synthesized. The images resulting from these manipulations were displayed on a calibrated 17–inch, RGB color monitor with flat screen controlled by a computer raster–graphics card providing 24 bits per pixel in true–color mode. In each experimental trial, the observer was presented with a pair of images, an original and a version with an exactly exponential luminance frequency distribution. The observer had to indicate the preferred image. Four observers with normal color vision participated. Results: All four observers preferred images with an exactly exponential luminance frequency distribution over the original images. Conclusions: Observers’ preference for images with exponential frequency distributions of luminance suggests that the visual system may be optimized for encoding this type of distribution.
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