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A tone mapping operator based on neural and psychophysical models of visual perception

机译:基于视觉感知的神经和心理物理模型的色调映射算子

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摘要

High dynamic range imaging techniques involve capturing and storing real world radiance values that span many orders of magnitude. However, common display devices can usually reproduce intensity ranges only up to two to three orders of magnitude. Therefore, in order to display a high dynamic range image on a low dynamic range screen, the dynamic range of the image needs to be compressed without losing details or introducing artefacts, and this process is called tone mapping. A good tone mapping operator must be able to produce a low dynamic range image that matches as much as possible the perception of the real world scene. We propose a two stage tone mapping approach, in which the first stage is a global method for range compression based on a gamma curve that equalizes the lightness histogram the best, and the second stage performs local contrast enhancement and color induction using neural activity models for the visual cortex. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
机译:高动态范围成像技术涉及捕获和存储跨越多个数量级的真实世界的辐射值。但是,普通的显示设备通常只能再现高达两到三个数量级的强度范围。因此,为了在低动态范围屏幕上显示高动态范围图像,需要在不丢失细节或引入伪影的情况下压缩图像的动态范围,该过程称为色调映射。一个好的色调映射运算符必须能够产生一个低动态范围图像,该图像应尽可能匹配真实世界场景的感知。我们提出了一种两阶段色调映射方法,其中第一阶段是基于伽玛曲线的范围压缩的全局方法,该伽玛曲线使亮度直方图最佳化,而第二阶段使用神经活动模型执行局部对比度增强和颜色归纳。视觉皮层。 ©(2015)版权所有,光电仪器工程师协会(SPIE)。摘要的下载仅允许个人使用。

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