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Preserving perceived brightness of displayed image over different illumination conditions

机译:在不同照明条件下保持显示图像的感知亮度

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In this paper, we propose an image correction method for preserving a brightness appearance of displayed images under several illumination conditions based on a novel human visual system (HVS) model named as a rod and cone response (RCR) model. The brightness appearance of displayed images changes according to an adaptation of human eyes caused by a surrounding illumination and characteristics of a display device, which is defined as a device model, such as a surface reflectance and a contrast ratio. The proposed method based on the RCR and the device model can predict the brightness appearance more precisely and faster than conventional HVS models such as CIECAM02. Our prototype display device with the proposed method reduces the prediction error by 81% with 12% of a computational cost compared to CIECAM02. The proposed method improves image quality on the display device under any surrounding illumination conditions.
机译:在本文中,我们提出了一种图像校正方法,该方法基于名为杆和锥响应(RCR)模型的新型人类视觉系统(HVS)模型,在几种照明条件下保持显示图像的亮度外观。显示的图像的亮度外观根据周围照明和显示设备的特性引起的人眼适应而变化,显示设备的特性被定义为设备模型,例如表面反射率和对比度。与传统的HVS模型(如CIECAM02)相比,基于RCR和设备模型的方法可以更准确,更快地预测亮度外观。与CIECAM02相比,采用该方法的原型显示设备将预测误差降低了81%,而计算成本却降低了12%。所提出的方法在任何周围照明条件下都改善了显示装置上的图像质量。

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