Modelling Surround-aware Contrast Sensitivity for HDR Displays

Despite advances in display technology, many existing applications rely on psychophysical datasets of human perception gathered using older, sometimes outdated displays. As a result, there exists the underlying assumption that such measurements can be carried over to the new viewing conditions of more modern technology. We have conducted a series of psychophysical experiments to explore contrast sensitivity using a state-of-the-art HDR display, taking into account not only the spatial frequency and luminance of the stimuli but also their surrounding luminance levels. From our data, we have derived a novel surroundaware contrast sensitivity function (CSF), which predicts human contrast sensitivity more accurately. We additionally provide a practical version that retains the benefits of our full model, while enabling easy backward compatibility and consistently producing good results across many existing applications that make use of CSF models. We show examples of effective HDR video compression using a transfer function derived from our CSF, tone-mapping, and improved accuracy in visual difference prediction

Perceptual image quality assessment for various viewing conditions and display systems

From complete darkness to direct sunlight, real-world dis- plays operate in various viewing conditions often resulting in a non-optimal viewing experience. Most existing Image Quality Assessment (IQA) methods, however, assume ideal environments and displays, and thus cannot be used when viewing conditions differ from the standard. In this paper, we investigate the influence of ambient illumination level and display luminance on human perception of image quality. We conduct a psychophysical study to collect a novel dataset of over 10000 image quality preference judgments performed in illumination conditions ranging from 0 lux to 20000 lux. We also propose a perceptual IQA framework that allows most existing image quality metrics (IQM) to accurately predict image quality for a wide range of illumination conditions and display parameters 1 . Our analysis demonstrates strong cor- relation between human IQA and the predictions of our proposed framework combined with multiple prominent IQMs and across a wide range of luminance values

High Dynamic Range (HDR) Display Perception

Displays have undergone a huge development in the last several decades. From cathode-ray tube (CRT), liquid crystal display (LCD), to organic light-emitting diode (OLED), even Q-OLED, the new configurations of the display bring more and more functions into industry and daily life. In the recent several years, high dynamic range (HDR) displays become popular. HDR displays usually refer to that the black level of the display is darker and the peak being brighter compared with the standard dynamic range (SDR) display. Traditionally, the peak luminance level can be used as the white in characterization and calibration. However, for HDR displays, the peak luminance is higher than the traditional diffuse white level. Exploration of the perceptual diffuse white in HDR image when presented in displays is proposed, which can be beneficial to the characterizing and the optimizing the usage of the HDR display. Moreover, in addition to the ``diffuse white , 3D color gamut volume can be calculated in some specific color appearance models. Calculation and modeling of the 3D color gamut volume can be very useful for display design and better characterizing display color reproduction capability. Furthermore, the perceptional color gamut volume can be measured through psychophysical experiments. Comparison between the perceptional color gamut volume and the theoretical 3D gamut volume calculations will reveal some insights for optimizing the usage of HDR displays. Another advantage of the HDR display is its darker black compared with the SDR display. Compared with the real black object, what level of black is `perfect\u27 enough in displays? Experiments were proposed and conducted to evaluate that if the HDR display is capable of showing ``perfect black for different types of background images/patterns. A glare-based model was proposed to predict the visual ``perfect black. Additionally, the dynamic range of human vision system is very large. However, the simultaneous dynamic range of human vision system is much smaller and is important for the fine tuning usage of HDR displays. The simultaneous dynamic range was measured directly for different stimulus sizes. Also, it was found that the simultaneous dynamic range was peak luminance level dependent. A mathematical model was proposed based on the experimental data to predict the simultaneous dynamic range. Also the spatial frequency effect of the target pattern on the simultaneous dynamic range was measured and modeled. The four different assessments about HDR displays perception would provide experimental data and models for a better understanding of HDR perception and tuning of the HDR display

Brilliance, contrast, colorfulness, and the perceived volume of device color gamut

With the advent of digital video and cinema media technologies, much more is possible in achieving brighter and more vibrant colors, colors that transcend our experience. The challenge is in the realization of these possibilities in an industry rooted in 1950s technology where color gamut is represented with little or no insight into the way an observer perceives color as a complex mixture of the observer’s intentions, desires, and interests. By today’s standards, five perceptual attributes – brightness, lightness, colorfulness, chroma, and hue - are believed to be required for a complete specification. As a compelling case for such a representation, a display system is demonstrated that is capable of displaying color beyond the realm of object color, perceptually even beyond the spectrum locus of pure color. All this begs the question: Just what is meant by perceptual gamut? To this end, the attributes of perceptual gamut are identified through psychometric testing and the color appearance models CIELAB and CIECAM02. Then, by way of demonstration, these attributes were manipulated to test their application in wide gamut displays. In concert with these perceptual attributes and their manipulation, Ralph M. Evans’ concept of brilliance as an attribute of perception that extends beyond the realm of everyday experience, and the theoretical studies of brilliance by Y. Nayatani, a method was developed for producing brighter, more colorful colors and deeper, darker colors with the aim of preserving object color perception – flesh tones in particular. The method was successfully demonstrated and tested in real images using psychophysical methods in the very real, practical application of expanding the gamut of sRGB into an emulation of the wide gamut, xvYCC encoding

Appearance-based image splitting for HDR display systems

High dynamic range displays that incorporate two optically-coupled image planes have recently been developed. This dual image plane design requires that a given HDR input image be split into two complementary standard dynamic range components that drive the coupled systems, therefore there existing image splitting issue. In this research, two types of HDR display systems (hardcopy and softcopy HDR display) are constructed to facilitate the study of HDR image splitting algorithm for building HDR displays. A new HDR image splitting algorithm which incorporates iCAM06 image appearance model is proposed, seeking to create displayed HDR images that can provide better image quality. The new algorithm has potential to improve image details perception, colorfulness and better gamut utilization. Finally, the performance of the new iCAM06-based HDR image splitting algorithm is evaluated and compared with widely spread luminance square root algorithm through psychophysical studies

Assessment of Quality of Experience of High Dynamic Range Images Using the EEG and Applications in Healthcare

File embargoed until 30.09.2021 at author's request.Recent years have witnessed the widespread application of High Dynamic Range (HDR) imaging, which like the Human Visual System (HVS), has the ability to capture a wide range of luminance values. Areas of application include home-entertainment, security, scientific imaging, video processing, computer graphics, multimedia communications, and healthcare. However, in practice, HDR content cannot be displayed in full on standard or low dynamic range (LDR) displays, and this diminishes the benefits of HDR technology for many users. To address this problem, Tone-Mapping Operators (TMO) are used to convert HDR images so that they can be displayed on low-dynamic-range displays and preserve as far as possible the perception of HDR. However, this may affect the visual Quality of Experience (QoE) of the end-user. QoE is a vital issue in image and video applications. It is important to understand how humans perceive quality in response to visual stimuli as this can potentially be exploited to develop and optimise image and video processing algorithms. Image consumption using mobile devices has become increasingly popular, given the availability of smartphones capable of producing and consuming HDR images along with advances in high-speed wireless communication networks. One of the most critical issues associated with mobile HDR image delivery services concerns how to maximise the QoE of the delivered content for users. An open research question therefore addresses how HDR images with different types of content perform on mobile phones. Traditionally, evaluation of the perceived quality of multimedia content is conducted using subjective opinion tests (i.e., explicitly), such as Mean Opinion Scores (MOS). However, it is difficult for the user to link the quality they are experiencing to the quality scale. Moreover, MOS does not give an insight into how the user feels at a physiological level in response to satisfaction or dissatisfaction with the perceived quality. To address this issue, measures that can be taken directly (implicitly) from the participant have now begun to attract interest. The electroencephalogram (EEG) is a promising approach that can be used to assess quality related processes implicitly. However, implicit QoE approaches are still at an early stage and further research is necessary to fully understand the nature of the recorded neural signals and their associations with user-perceived quality. Nevertheless, the EEG is expected to provide additional and complementary information that will aid understanding of the human perception of content. Furthermore, it has the potential to facilitate real-time monitoring of QoE without the need for explicit rating activities. The main aim of this project was therefore to assess the QoE of HDR images employing a physiological method and to investigate its potential application in the field of healthcare. This resulted in the following five main contributions to the research literature: 1. A detailed understanding of the relationship between the subjective and objective evaluation of the most popular TMOs used for colour and greyscale HDR images. Different mobile displays and resolutions were therefore presented under normal viewing conditions for the end-user with an LDR display as a reference. Preliminary results show that, compared to computer displays, small screen devices (SSDs) such as those used in smartphones impact the performance of TMOs in that a higher resolution gave more favourable MOS results. 2. The development of a novel Electrophysiology-based QoE assessment of HDR image quality that can be used to predict perceived image quality. This was achieved by investigating the relationships between changes in EEG features and subjective quality test scores (i.e. MOS) for HDR images viewed with SSD. 3. The development of a novel QoE prediction model, based on the above findings. The model can predict user acceptability and satisfaction for various mobile HDR image scenarios based on delta-beta coupling. Subjective quality tests were conducted to develop and evaluate the model, where the HDR image quality was predicted in terms of MOS. 4. The development of a new method of detecting a colour vision deficiency (CVD) using EEG and HDR images. The results suggest that this method may provide an accurate way to detect CVD with high sensitivity and specificity (close to 100%). Potentially, the method may facilitate the development of a low-cost tool suitable for CVD diagnosis in younger people. 5. The development of an approach that enhances the quality of dental x-ray images. This uses the concepts of QoE in HDR images without re-exposing patients to ionising radiation, thus improving patient care. Potentially, the method provides the basis for an intelligent model that accurately predicts the quality of dental images. Such a model can be embedded into a tool to automatically enhance poor quality dental images.Ministry of Higher Education and Scientific Research (MoHESR