基于感知的直方图均衡化色调映射应用

Stelios E. Ploumis, Ronan Boitard, M. Pourazad, P. Nasiopoulos
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引用次数: 6

摘要

由于高动态范围(HDR)内容和显示器的商业可用性不断增加,HDR内容与标准动态范围显示器的向后兼容性目前是一个非常重要的话题。多年来,已经提出了大量的色调映射算子(TMOs),以使HDR内容适应SDR显示器的有限功能。其中,直方图均衡化(Histogram Equalization, HE)被认为可以在广泛的图像集上提供良好的效果。然而,当HDR图像具有较大的统一区域(即天空)时,naïve应用HE会导致带状伪影或噪声放大。为了在均匀背景或黑暗区域中区分相关信息和噪声,作者提出了一个上限函数。他们的方法产生了无噪声但模糊的图像。本文提出了一种基于感知量化器(PQ)函数的天花板函数。我们的方法使用PQ在原始HDR图像的亮度范围上分配的码字数和生成的SDR图像中相应的码字数作为阈值。我们限制SDR上的码字数量等于或少于HDR。在天花板操作期间保存的码字被重新分配,以增加对比度以及最终图像的亮度。结果表明,该方法得到的SDR图像具有较好的无噪性和亮度。最后,由于该方法是全局TMO,因此复杂度低,适合于实时应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perception-based Histogram Equalization for tone mapping applications
Due to the ever increasing commercial availability of High Dynamic Range (HDR) content and displays, backward compatibility of HDR content with Standard Dynamic Range displays is currently a topic of high importance. Over the years, a significant amount of Tone Mapping Operators (TMOs) have been proposed to adapt HDR content to the restricted capabilities of SDR displays. Among them, the Histogram Equalization (HE) is considered to provide good results for a wide set of images. However, the naïve application of HE results either in banding artifacts or noise amplification when the HDR image has large unified areas (i.e. sky). In order to differentiate relevant information from noise in a uniform background, or in dark areas, the authors proposed a ceiling function. Their method results in noise-free but dim images. In this paper we propose a novel ceiling function which is based on the Perceptual Quantizer (PQ) function. Our method uses as threshold the number of code-words that PQ assigns on a luminance range in the original HDR image and the corresponding number of code-words in the resulting SDR image. We limit the number of code-words on SDR to be equal or less than the HDR. The saved code-words during the ceiling operation are redistributed to increase the contrast as well as the brightness of the final image. Results shows that provided SDR images are noise-free and brighter than the one obtained with prior HE operators. Finally since the proposed method is a Global TMO, it is thereby of low complexity and suitable for real time applications.
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