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Effective Channel-Independent Inverse Characterization Method for Display Device

机译:用于显示装置的有效的与通道无关的逆表征方法

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This paper proposes a channel-independent inverse characterization process based on the GOG model for a display device. The CIEXYZ values for each of RGB channel can estimated from nine channel-independent interpolation TRCs (Tone Response Curves), and the result of this characterization method is better than that from conventional three channel-independent interpolation TRCs. However inverse characterization is impossible when using nine channel-independent interpolation TRCs, as the CIEXYZ values that correspond to each RGB values are inseparable directly. Accordingly, inverse characterization is usually implemented using the 3D-LUT (Look-Up Table) method. Yet, although the result of a 3D-LUT is accurate, creating the LUT requires a lot of memory space and considerable amount of measurements. Therefore, an accurate inverse characterization method is proposed based on the simple modeling of channel-dependent values and nine channel inverse processes based on the GOG model. CIEXYZ values are computed for three normalized luminance values using an inverse matrix. The channel-dependent values are subtracted from the normalized luminance values that are generated by an overlapped spectral distribution of the primary digital values based on modeling the channel-dependent values. Each of the three normalized luminance values is modified into the corresponding nine channel TRCs using a gamma correction of each channel and modifying the tone response curve. The digital values are estimated by the nine channel-independent interpolation TRCs based on an inverse GOG model using the parameters of forward characterization, considering weighting factors. Three digital values are determined for each RGB channel based on the maximum CIEXYZ values for each red, green, and blue channel. As such, the proposed method reduces the time complexity and number of measurements required for accuracy.
机译:本文提出了一种基于GOG模型的显示装置的通道无关逆表征方法。可以从9个独立于通道的内插TRC(音调响应曲线)中估算每个RGB通道的CIEXYZ值,并且这种表征方法的结果要好于常规3个独立于通道的内插TRC。但是,当使用九个独立于通道的内插TRC时,反向表征是不可能的,因为与每个RGB值相对应的CIEXYZ值是直接不可分割的。因此,通常使用3D-LUT(查找表)方法来实现逆表征。然而,尽管3D-LUT的结果是准确的,但创建LUT仍需要大量的存储空间和大量的测量。因此,基于对通道相关值的简单建模和基于GOG模型的九个通道逆过程,提出了一种精确的逆表征方法。使用逆矩阵为三个归一化的亮度值计算CIEXYZ值。基于对通道相关值的建模,从由主要数字值的重叠光谱分布生成的归一化亮度值中减去通道相关值。使用每个通道的伽马校正并修改色调响应曲线,将三个标准化亮度值中的每一个都修改为相应的九个通道TRC。在考虑到加权因子的情况下,使用前向表征参数,基于逆GOG模型,由九个独立于通道的内插TRC估计数字值。基于每个红色,绿色和蓝色通道的最大CIEXYZ值,为每个RGB通道确定三个数字值。这样,所提出的方法降低了时间复杂度和准确性所需的测量次数。

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