Color restoration of lighting scenes with locally adapted HDR images

Yuto Kubo, Takao Jinno, Shigeru Kuriyama
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Abstract

Images of scenes illuminated by colored lightings are often degraded owing to the clipped whites and crushed shadows caused by the lack of dynamic range. Such degradation can be improved by introducing high dynamic range (HDR) images that can fully capture the brightness and color at a large bit-depth. Color appearance model (CAM) is widely used for accurately restoring colors, by replicating the property of human vision that can adaptively recognize colors according to the brightness within a local region. This local adaptation model, however, is inapplicable to lighting scenes where the spatial variation of brightness becomes large. We propose a method of combining such local adaptations separately applied for different regions on a single image. This method tries to restore the color of HDR images while retaining the global consistency of brightness variations. The effectiveness of our method is experimentally demonstrated for the indoor scene illuminated by a color LED.
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用局部适应的HDR图像恢复灯光场景的色彩
彩色灯光照射下的景物,由于缺乏动态范围,往往会造成白的剪切和阴影的破碎,从而使图像质量下降。这种退化可以通过引入高动态范围(HDR)图像来改善,该图像可以在大位深下完全捕获亮度和颜色。颜色外观模型(Color appearance model, CAM)是一种广泛应用于精确还原颜色的方法,它复制了人类视觉根据局部区域内亮度自适应识别颜色的特性。然而,这种局部适应模型不适用于亮度空间变化较大的照明场景。我们提出了一种将这些局部适应分别应用于单个图像上的不同区域的方法。该方法试图在保持亮度变化全局一致性的同时,还原HDR图像的色彩。对彩色LED照明的室内场景进行了实验验证。
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