Song Yang, Jiang Gangyi, Yu Mei, Zhang Yun, Shao Feng, Peng Zongju
Appl Opt. 2016 Dec 10;55(35):10084-10091. doi: 10.1364/AO.55.010084.
High dynamic range (HDR) images can only be backward-compatible with existing low dynamic range (LDR) imaging systems after being processed by tone-mapping operators. Hence, the quality assessment (QA) of tone-mapped HDR images has become an important and challenging issue in HDR imaging research. In this paper, we propose a naturalness index for a tone-mapped image to predict its quality. First, we extract the statistical features of the tone-mapped image's luminance value and use it to evaluate the brightness naturalness with no reference information. Meanwhile, we use perceptive color, image contrast, and detail information to represent the image content and predict their naturalness qualities, respectively. Then, the four components of the naturalness qualities are combined to yield the overall naturalness quality of the tone-mapped image. Experimental results on a publicly available database demonstrated that, in comparison with a traditional LDR image QA method and a leading tone-mapped image QA method, the proposed method has better performance in evaluating a tone-mapped image's quality.
高动态范围(HDR)图像在经过色调映射算子处理后,才能与现有的低动态范围(LDR)成像系统实现向后兼容。因此,色调映射后的HDR图像的质量评估(QA)已成为HDR成像研究中的一个重要且具有挑战性的问题。在本文中,我们提出了一种用于色调映射图像的自然度指数,以预测其质量。首先,我们提取色调映射图像亮度值的统计特征,并利用它在无参考信息的情况下评估亮度自然度。同时,我们分别使用感知颜色、图像对比度和细节信息来表示图像内容,并预测它们的自然度质量。然后,将自然度质量的四个分量组合起来,得到色调映射图像的整体自然度质量。在一个公开可用数据库上的实验结果表明,与传统的LDR图像QA方法和领先的色调映射图像QA方法相比,所提出的方法在评估色调映射图像的质量方面具有更好的性能。