A review on high dynamic range (HDR) image quality assessment

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC International Journal on Smart Sensing and Intelligent Systems Pub Date : 2021-01-01 DOI:10.21307/ijssis-2021-010
I. Gunawan, Ocarina Cloramidina, Salmaa Badriatu Syafa’ah, Rizcy Hafivah Febriani, G. P. Kuntarto, B. I. Santoso
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引用次数: 2

Abstract

Abstract This paper presents a literature review on the method of measuring high dynamic range (HDR) image quality. HDR technology can help maximize user satisfaction level when using HDR images-based visual services. The advance of HDR technology indirectly presents a more difficult challenge to the image quality assessment method due to the high sensitivity of the human visual system (HVS) to various kinds of distortions that may arise in HDR images. This is related to the process of HDR image generation, which in general can be classified into two broad categories: the formation using the multiple exposure fusion (MEF) method and the inverse tone mapping operator (ITMO) method. In this paper, we will outline how HDR image quality measurement method works and describe some examples of these measurement methods which are related to the way the HDR images are fabricated. From these methods, it can be seen that most of them are still focused on full-reference and no-reference quality models. We argue that there is still room for the development of reduced-reference HDR image quality assessment.
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高动态范围(HDR)图像质量评价综述
摘要本文对高动态范围(HDR)图像质量的测量方法进行了文献综述。当使用基于HDR图像的视觉服务时,HDR技术可以帮助最大限度地提高用户满意度。由于人类视觉系统(HVS)对HDR图像中可能出现的各种失真的高灵敏度,HDR技术的进步间接地对图像质量评估方法提出了更困难的挑战。这与HDR图像生成过程有关,HDR图像通常可分为两大类:使用多重曝光融合(MEF)方法和逆色调映射算子(ITMO)方法形成。在本文中,我们将概述HDR图像质量测量方法的工作原理,并描述这些测量方法的一些例子,这些方法与HDR图像的制作方式有关。从这些方法中可以看出,大多数方法仍然侧重于完全参考和无参考质量模型。我们认为,减少参考HDR图像质量评估仍有发展空间。
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来源期刊
CiteScore
2.70
自引率
8.30%
发文量
15
审稿时长
8 weeks
期刊介绍: nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity
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