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首页> 外文会议>Twenty-fifth color and imaging conference : Color science and engineering systems, technologies, and applications >PuRet:Material Appearance Enhancement Considering Pupil and Retina Behaviors
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PuRet:Material Appearance Enhancement Considering Pupil and Retina Behaviors

机译：PuRet：考虑到瞳孔和视网膜行为的材料外观增强

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摘要

In addition to colors and shapes, factors of materialrnappearance such as glossiness, translucency, and roughness arernimportant for reproducing the realistic feeling of images. In general,rnthese perceptual qualities are often degraded when reproducedrnas digital color images. Therefore, it is useful to enhance andrnreproduce them. In this article, the authors propose a materialrnappearance enhancement algorithm for digital color images. First,rnthey focus on the change of pupil behaviors, which is the first of thernearly vision systems to recognize visual information. According torntheir psychophysiological measurement of pupil size during materialrnobservation, they find that careful observation of surface appearancerncauses the pupil size to contract further. Next, they reflect thisrnproperty in the retinal response, which is the next system in earlyrnvision. Then, they construct a material appearance enhancementrnalgorithm named “PuRet” based on these physiological models ofrnpupil and retina. By applying the PuRet algorithm to digital color testrnimages, they confirm that perceived material appearance, includingrnglossiness, transparency, and roughness, in the images is enhancedrnby using their PuRet algorithm. Furthermore, they show possibilitiesrnto apply their algorithm to a material appearance managementrnsystem that could produce equivalent appearance qualities amongrndifferent imaging devices by adjusting one parameter of PuRet.
机译：除了颜色和形状以外，诸如再现性，半透明性和粗糙度之类的材料外观因素对于再现图像的逼真的感觉也很重要。通常，当再现数码彩色图像时，这些感知质量通常会降低。因此，增强和复制它们是有用的。在本文中，作者提出了一种用于数字彩色图像的外观增强算法。首先，他们关注瞳孔行为的变化，这是最早的视觉系统识别视觉信息。根据他们在进行材料检查时对瞳孔大小的心理生理测量，他们发现仔细观察表面外观会导致瞳孔大小进一步收缩。接下来，它们在视网膜反应中反映了这种特性，这是早期视觉中的下一个系统。然后，他们基于瞳孔和视网膜的这些生理模型，构建了一种名为“ PuRet”的物质外观增强算法。通过将PuRet算法应用于数字彩色测试图像，他们确认使用其PuRet算法可以增强图像中感知到的材料外观，包括光泽度，透明度和粗糙度。此外，他们展示了将其算法应用于材料外观管理系统的可能性，该系统可以通过调整PuRet的一个参数在不同的成像设备之间产生相同的外观质量。

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