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

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 noreference quality models. We argue that there is still room for the development of reduced-reference HDR image quality assessment.

Efficient Computational Cost Saving in Video Processing for QoE Estimation

“…The development of an objective video metric that accurately estimates the perceived video quality is still challenging nowadays. Not only because of the task of finding an algorithm whose quality prediction is in good agreement with subjective scores from real human observers [8], but also because of the emergence of new types of content and applications that are clearly differentiated from traditional audiovisual content, and require the design of specific video metrics: User-Generated content (UGC) [9], High Dynamic Range (HDR) audiovisual content [10], [11], omnidirectional videos [12], [13], [14], [15], videogames [16], and artificial and enhanced videos [17], [18], [19].…”

Multiple Sensor based Human Detection Robots: A Review

“…The network is optimized for real-time performance on NVIDIA's Jetson TX2, enabling a survivor detection system on DJI Matrice 210 and Manifold 2-G for post-disaster SAR operations. As emphasized by Gunawan et al [43], methods for measuring high dynamic range (HDR) image quality are crucial for enhancing user satisfaction in HDR-based visual services. The high sensitivity of the human visual system to distortions in HDR images poses a challenge.…”