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We developed a quantitative evaluation method for luminance and color uniformity on a display screen. In this paper, we report the analysis result of a viewer perception of luminance and color uniformity. In experiments, observers subjectively evaluated Mura images which were showed on the light emitting diode (LED) backlight screen by adjusting the luminance of each LED. We measured the luminance and color distributions of the Mura images by a 2D colorimeter, then, the measured data was converted into S-CIELAB. In S-CIELAB calculations, two dimensional MTF (Modulation Transfer Function) of human eye were used in which anisotropic properties of the spatial frequency response of human vision were considered. Some indexes for a quantitative evaluation model were extracted by the image processing. The significant indexes were determined by the multiple regression analysis to quantify the degree of uniformity of the backlight screen. The luminance uniformity evaluation model and color uniformity evaluation model were derived from this analysis independently. In addition, by integrating both of these models we derived a quantitative evaluation model for luminance and color unevenness simultaneously existing on the screen.
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Kunihiko NAGAMINE, Satoshi TOMIOKA, Tohru TAMURA, Yoshihide SHIMPUKU, "A Quantitative Evaluation Method for Luminance and Color Uniformity of a Display Screen Based on Human Perception" in IEICE TRANSACTIONS on Electronics,
vol. E95-C, no. 11, pp. 1699-1706, November 2012, doi: 10.1587/transele.E95.C.1699.
Abstract: We developed a quantitative evaluation method for luminance and color uniformity on a display screen. In this paper, we report the analysis result of a viewer perception of luminance and color uniformity. In experiments, observers subjectively evaluated Mura images which were showed on the light emitting diode (LED) backlight screen by adjusting the luminance of each LED. We measured the luminance and color distributions of the Mura images by a 2D colorimeter, then, the measured data was converted into S-CIELAB. In S-CIELAB calculations, two dimensional MTF (Modulation Transfer Function) of human eye were used in which anisotropic properties of the spatial frequency response of human vision were considered. Some indexes for a quantitative evaluation model were extracted by the image processing. The significant indexes were determined by the multiple regression analysis to quantify the degree of uniformity of the backlight screen. The luminance uniformity evaluation model and color uniformity evaluation model were derived from this analysis independently. In addition, by integrating both of these models we derived a quantitative evaluation model for luminance and color unevenness simultaneously existing on the screen.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.E95.C.1699/_p
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@ARTICLE{e95-c_11_1699,
author={Kunihiko NAGAMINE, Satoshi TOMIOKA, Tohru TAMURA, Yoshihide SHIMPUKU, },
journal={IEICE TRANSACTIONS on Electronics},
title={A Quantitative Evaluation Method for Luminance and Color Uniformity of a Display Screen Based on Human Perception},
year={2012},
volume={E95-C},
number={11},
pages={1699-1706},
abstract={We developed a quantitative evaluation method for luminance and color uniformity on a display screen. In this paper, we report the analysis result of a viewer perception of luminance and color uniformity. In experiments, observers subjectively evaluated Mura images which were showed on the light emitting diode (LED) backlight screen by adjusting the luminance of each LED. We measured the luminance and color distributions of the Mura images by a 2D colorimeter, then, the measured data was converted into S-CIELAB. In S-CIELAB calculations, two dimensional MTF (Modulation Transfer Function) of human eye were used in which anisotropic properties of the spatial frequency response of human vision were considered. Some indexes for a quantitative evaluation model were extracted by the image processing. The significant indexes were determined by the multiple regression analysis to quantify the degree of uniformity of the backlight screen. The luminance uniformity evaluation model and color uniformity evaluation model were derived from this analysis independently. In addition, by integrating both of these models we derived a quantitative evaluation model for luminance and color unevenness simultaneously existing on the screen.},
keywords={},
doi={10.1587/transele.E95.C.1699},
ISSN={1745-1353},
month={November},}
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TY - JOUR
TI - A Quantitative Evaluation Method for Luminance and Color Uniformity of a Display Screen Based on Human Perception
T2 - IEICE TRANSACTIONS on Electronics
SP - 1699
EP - 1706
AU - Kunihiko NAGAMINE
AU - Satoshi TOMIOKA
AU - Tohru TAMURA
AU - Yoshihide SHIMPUKU
PY - 2012
DO - 10.1587/transele.E95.C.1699
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E95-C
IS - 11
JA - IEICE TRANSACTIONS on Electronics
Y1 - November 2012
AB - We developed a quantitative evaluation method for luminance and color uniformity on a display screen. In this paper, we report the analysis result of a viewer perception of luminance and color uniformity. In experiments, observers subjectively evaluated Mura images which were showed on the light emitting diode (LED) backlight screen by adjusting the luminance of each LED. We measured the luminance and color distributions of the Mura images by a 2D colorimeter, then, the measured data was converted into S-CIELAB. In S-CIELAB calculations, two dimensional MTF (Modulation Transfer Function) of human eye were used in which anisotropic properties of the spatial frequency response of human vision were considered. Some indexes for a quantitative evaluation model were extracted by the image processing. The significant indexes were determined by the multiple regression analysis to quantify the degree of uniformity of the backlight screen. The luminance uniformity evaluation model and color uniformity evaluation model were derived from this analysis independently. In addition, by integrating both of these models we derived a quantitative evaluation model for luminance and color unevenness simultaneously existing on the screen.
ER -