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A LUT-based Method for Recovering Color Signals from High Dynamic Range Images

机译:一种基于LUT的方法,用于从高动态范围图像中恢复颜色信号

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This paper describes an effective method for recovering color signals from multiband images of a high dynamic range (HDR) scene. We note that the color signals in a natural scene have the HDR characteristic of luminance level from very dark shadow area to highly bright sky. The Wiener estimator can be used for estimating spectral-power distributions of the color signals from HDR image data. A previous study presented an improved Wiener estimator for addressing accurate color signal estimation in HDR scenes. However, the previous method required the pixel-by-pixel estimation of parameters contained in the Wiener estimator, which resulted in requiring much computation time. For fast computation, therefore, we propose a lookup-table-based (LUT-based) estimation method for color signals in HDR scenes. In the preliminary stage in advance of color signal estimation, we prepare LUT of the statistical matrix needed in the Wiener estimator, consisting of the covariance matrix of color signals and imaging noises. In the stage of color signal estimation, the estimates are obtained pixel by pixel by the Wiener estimator with the most suitable matrix selected from the LUT. For validating the proposed method, experiments are conducted using actual HDR scenes. Experimental results show the superiority of our method in computation time to the previous methods, with keeping estimation accuracy.
机译:本文介绍了一种从高动态范围(HDR)场景的多频带图像中恢复彩色信号的有效方法。我们注意到自然场景中的颜色信号具有从非常暗影区域到高度亮天的亮度水平的HDR特征。维纳估计器可用于估计来自HDR图像数据的颜色信号的光谱功率分布。先前的研究提出了一种改进的维纳估计器,用于解决HDR场景中的准确彩色信号估计。然而,先前的方法需要维纳估计器中包含的参数的像素逐像素估计,这导致需要大量计算时间。因此,对于快速计算,我们提出了一种基于查找表的(基于LUT的)估计方法,用于HDR场景中的颜色信号。在彩色信号估计前进的初步阶段,我们准备了维纳估计器中所需的统计矩阵的LUT,由颜色信号和成像噪声的协方差矩阵组成。在彩色信号估计的阶段,估计由维纳估计器获得像素的像素,其中具有从LUT中选择的最合适的矩阵。为了验证所提出的方法,使用实际的HDR场景进行实验。实验结果表明我们在计算时间到以前方法的方法的优越性,保持估计精度。

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