54.2: A High Dynamic Range Display Using Low and High Resolution Modulators

Technique of high dynamic range imaging (HDRI) was introduced into conventional high dynamic range display (HDRD). Sharpness of image was further enhanced by improving local contrast ratio in the HDRI-based high dynamic range display.

Current HDR display technology approaches the dynamic range of the fully adapted human vision system. As such, this technology has potential for performing as a surrogate for realworld scenes in the evaluation of the accuracy of high dynamic range (HDR) algorithms that map HDR scenes to the more common, everyday display technology having limited dynamic range. Clearly, use of HDR display technology has the benefit of simplicity in experimental design while maintaining the high dynamic range of the original scene. To evaluate this potential use for HDR displays, seven published versions of well-known tone mapping algorithms were benchmarked for rendering accuracy against each of four real-world scenes constructed in the lab and their corresponding renderings on the Munsell Color Science Laboratory's (MCSL) HDR display. The results between those obtained from the MCSL HDR display and those obtained from the real-world scenes are in good agreement thus validating the HDR display's potential as an evaluation tool in this context.

In this paper we present a new technique for the display of High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as reference, that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO.

Tone-mapping-operators (TMOs) provide a useful means for converting high dynamic range (HDR) images to low dynamic range (LDR) images so that they can be viewed on standard displays, but this may influence the visual quality of experience (QoE) of the end-user. There is a need to understand the impact of TMOs to inform the choice of TMO algorithms for different displays, especially for small-screen-devices (SSDs) such as those used in mobile phones. This is important, as mobile devices are becoming the primary means of consuming multimedia contents. However, few studies have been undertaken to assess the impact of TMOs and viewing devices (especially SSDs) on the visual QoE of the user when using. In this chapter, we evaluate subjectively and objectively, the commonly used TMOs in different displays and resolutions for colour and grey-scale HDR images. Our results show that viewing devices have an influence on the TMOs performance, suggesting the need for a careful choice of TMO to enhance the viewing-QoE of the end-user. As expected, the higher resolution, the better HDR-image quality. Surprisingly, there was no significant difference between the Mean of Opinion Score (MOS) scores for colour and grey-scale images in SSDs. The device and TMOs affect QoE for colour and grey HDR-image equally. We found Shannon entropy (SE) to be a good objective measure of quality for colour and grey HDR images, suggesting that entropy may find use in automated HDR quality control assessment schemes, while; HDR-VDP-2 is a good objective measure for colour HDR image only.

High dynamic range (HDR) displays with dual-panels are one type of displays that can provide HDR content. These are composed of a white backlight panel and a colour LCD panel. Local dimming algorithms are used to control the backlight panel in order to reproduce content with high dynamic range and contrast at a high fidelity. However, existing local dimming algorithms usually process low dynamic range (LDR) images, which are not suitable for processing HDR images. In addition, these methods use hand-crafted features to estimate the backlight values, which may not be suitable for many kind of images. In this work, a novel deep learning based local dimming method is proposed for rendering HDR images on dual-panel HDR displays. The method uses a Convolutional Neural Network (CNN) to directly predict backlight values, using as input the HDR image that is to be displayed. The model is designed and trained via a controllable power parameter that allows a user to trade off between power and quality. The proposed method is evaluated against seven other methods on a test set of 105 HDR images, using a variety of quantitative quality metrics. Results demonstrate improved display quality and better power consumption when using the proposed method compared to the best alternatives.

Using evolutionary population synthesis, we present high-resolution (0.3 angstrom) integrated spectral energy distributions from 3000 to 7000 angstrom and absorption-line indices defined by the Lick Observatory Image Dissector Scanner (Lick/IDS) system, for an extensive set of instantaneous-burst binary stellar populations with binary interactions. The ages of the populations are in the range 1-15 Gyr and the metallicities are in the range 0.004-0.03. These high-resolution synthesis results can satisfy the needs of modern spectroscopic galaxy surveys, and are available on request. By comparing the synthetic continuum of populations at high and low resolution, we show that there is good agreement for solar metallicity and tolerable disagreement for non- solar metallicity. The strength of the Balmer lines at high spectral resolution is greater than that at low resolution for all metallicities. The comparison of Lick/IDS absorption-line indices at low and high resolution, both of which are obtained by the fitting functions, shows that the discrepancies in all indices except for TiO1 and TiO2 are insignificant for populations with Z = 0.004 and 0.02. The high-resolution Ca4227, Fe5015 and Mg-b indices are redder than the corresponding low-resolution ones for populations with Z = 0.01 and 0.03; this effect lowers the derived age and metallicity of the population. The high-resolution Mg-1, Fe5709 and Fe5782 indices are bluer than those at low resolution; this effect raises the age and metallicity. The discrepancy in these six indices is greater for populations with Z = 0.03 in comparison to Z = 0.01. At high resolution we compare the Lick/IDS spectral absorption indices obtained by using the fitting functions with those measured directly from the synthetic spectra. We find that the Ca4455, Fe4668, Mg-b and Na D indices obtained by the use of the fitting functions are redder for all metallicities, Fe5709 is redder at Z = 0.03 and becomes bluer at Z = 0.01 and 0.004, and the other indices are bluer for all metallicities than the corresponding values measured directly from the synthetic spectra.

Typical digital cameras exhibit a limitation regarding the dynamic range of the scene radiance they can capture. High Dynamic Range (HDR) imaging refers to methods and systems that aim to generate images that exhibit higher dynamic range between the lightest and the darkest parts of the an image. A typical approach for generating HDR images is exposure bracketing where multiple frames, each one with a different exposure setting, are captured and combined to a HDR image of the scene. The large number of images that exposure bracketing requires often leads to motion artefacts that limit the visual quality of the resulting HDR image. In this work, we propose a novel approach in HDR imaging that significantly reduces the necessary number of images. In our proposed system, we employ the notion of random exposure where each pixel of a single frame collects light for a random amount of time. By collecting a small number of such images, the full sequence of low dynamic range images can be reconstructed and subsequently used for HDR generation. The problem is solved by casting the reconstruction of the sequence as a nuclear norm minimization problem following the premises of the recently proposed theory of Matrix Completion. Experimental results suggest that the proposed method is able to reconstruct the sequence from as low as 20% of the images that traditional techniques require with minimal reduction in image quality.

Abstract. Nowadays, Terrestrial Laser Scanning (TLS) technology is gaining popularity in monitoring and predicting the movement of landslide due to the capability of high-speed data capture without requiring a direct contact with the monitored surface. It offers very high density of point cloud data in high resolution and also can be an effective tool in detecting the surface movement of the landslide area. The aim of this research is to determine the optimal level of scanning resolution for landslide monitoring using TLS. The Topcon Geodetic Laser Scanner (GLS) 2000 was used in this research to obtain the three dimensional (3D) point cloud data of the landslide area. Four types of resolution were used during scanning operation which were consist of very high, high, medium and low resolutions. After done with the data collection, the point clouds datasets were undergone the process of registration and filtering using ScanMaster software. After that, the registered point clouds datasets were analyzed using CloudCompare software. Based on the results obtained, the accuracy of TLS point cloud data between picking point manually and computed automatically by ScanMaster software shows the maximum Root Mean Square (RMS) value of coordinate differences were 0.013 m in very high resolution, 0.017 m in high resolution, 0.031 m in medium resolution and 0.052 m in low resolution respectively. Meanwhile, the accuracy of TLS point cloud data between picking point manually and total station data using intersection method shows the maximum RMS values of coordinate differences were 0.013 m in very high resolution, 0.018 m in high resolution, 0.033 m in medium resolution and 0.054 m in low resolution respectively. Hence, it can be concluded that the high or very high resolution is needed for landslide monitoring using Topcon GLS-2000 which can provide more accurate data in slope result, while the low and medium resolutions is not suitable for landslide monitoring due to the accuracy of TLS point cloud data that will decreased when the resolution value is increased.

Emerging display technologies are proposing monitors for medical imaging with an extended dynamic range of luminance. Those devices offer the opportunity to extend the range of visual information displayed, but the limits of the human visual system (HVS) in perceiving such information can cancel the advantages. To investigate this problem, we present a set of experiments, to assess the visual response of the HVS to controlled high dynamic range (HDR) content. They analyse the effects of glare. Using a typical HDR display, tailored for medical imaging applications, they first study the dependence of the visible dynamic range from the inter‐ocular glare, induced by different backgrounds, then the effect of glare on the detection of test elements on medical radiographic images. Finally, they assess the influence of luminance‐equivalent backgrounds with different structure in the detection of test patches. The results of the experiments confirm the glare as a major player in influencing visual information detection. Glare has a significant impact in limiting the amount of visual information actually perceived, consequently limiting analysis capabilities of such images. This confirms the importance of investigating and considering the characteristics of human vision in the design and test of HDR imaging systems.

With a rising trend to use optical fiber in both short-reach and long-haul network applications, it has become necessary to detect faults with high spatial resolution, sensitivity, and dynamic range in industry. Unfortunately, the most widely used diagnostic technique, optical time-domain reflectometry (OTDR), has an inherent trade-off between the above mentioned figures of merit. Consequently, traditional OTDR systems can either be used in short-reach applications with high spatial resolution or long-haul applications with high dynamic range. Both OTDR and optical frequency-domain reflectometry systems have been proposed in the past which can arguably close the gap between the two extremes, but they also have a trade-off with the cost, form-factor, and complexity. Recently, researchers have demonstrated an input/output (I/O) interface integrated OTDR (iOTDR), which uses digital I/O ports to perform OTDR measurements with high spatial and voltage resolution. The iOTDR eliminates the necessity of using high-end analog-to-digital converters and demonstrates its potential to be fully integrated in an optical switch with minimum hardware modification. Additionally, the iOTDR is also reconfigurable and software-defined, making it a power- and resource-efficient solution. Thus, it is especially attractive for short-distance communication links, such as those in a datacenter, where computational resources are limited. This manuscript expands upon the advantages brought upon by the iOTDR to propose and demonstrate a new versatile iOTDR that can achieve high spatial resolution, sensitivity, and dynamic range for both short-reach and long-haul networks thanks to its highly reconfigurable design.

How does distraction from a laser strike impact the visual performance of aircrew? While laser incidents against commercial aircraft are commonplace (7,025 were reported to the Federal Aviation Authority in 2021), only a relatively small percentage result in laser light entering the cockpit and causing laser eye dazzle. The vast majority of incidents pose a more significant ‘distraction’ risk, with the potential to severely compromise safety if experienced during critical phases of flight. Previous work by the US Air Force Research Laboratory (AFRL) used laser exposures in the peripheral visual field of human participants performing a discrimination task involving central and peripheral vision. The results showed a degradation in task performance in the presence of laser distractions. The current study used a similar experimental paradigm, but both the task and the distraction were presented on a High Dynamic Range (HDR) display. This paper will detail the experimental setup and data collection, together with results to quantify how bright light distractions affect visual performance. A comparison to the AFRL study will be used to assess whether a HDR display can be used as a more flexible alternative to laser exposures for such experiments. The contents include material subject to © Crown copyright (2022), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk.

In the real world the contrast between bright areas, directly illuminated by the sun, and dark shadows can be of 6 or 7 orders of magnitude. Although such huge contrast ratio is common in the natural world when these luminance levels are to be displayed on a typical monitor, the range is far too large. Bright areas appear overly saturated and shadows are displayed as black. Until recently, the only approach to solve this problem was to compress the luminance component of a high dynamic range (HDR) scene. Such techniques are known as tone mapping. However, even tone mapping operators are not always capable of producing sufficient contrast reduction. In this paper we present the results of a psychophysical investigation to validate a novel HDR display which is capable of contrast ratios similar to what is present in the physical world. Images displayed on this device are an accurate representation of a window on a scene and may not be equivalent as standing in the real scene due to a lack of peripheral information. We describe three perceptual studies with the goal of validating the device against real scenes in terms of peripheral vision.

The measurement accuracy and reliability of thermography are largely limited by a relatively low spatial resolution of the thermal imager. Using a high-end camera to achieve high spatial resolution can be expensive or infeasible as a high sample rate is required. Furthermore, system miniaturization becomes an inevitable trend with the continuous development of the Internet of Things (IoT) and their suitability to in situ inspection scenarios. However, a miniaturized sensor usually suffers from low spatial resolution. Addressing this challenge, this article reports a novel spatial resolution enhancement for a thermogram (SRE4T) system to significantly improve the spatial resolution without upgrading the sensor. A high-resolution (HR) thermal image is reconstructed by fusing a sequence of low-resolution (LR) images with subpixel movements. To achieve the best image quality, instead of benefiting from natural movements of the existing studies, this article proposes to use an HR xy translation stage to produce a sequence of controlled subpixel movements. The performance of the proposed system was tested on both high-end and low-end thermal imagers. Both visual and quantitative results successfully demonstrated the considerable improvement of the quality of thermal images [up to 30.5% improvement of the peak signal-to-noise ratio (PSNR)]. This technique allows improving the measurement accuracy of thermography inspection without upgrading sensors. It also has potential to be applied on other imaging systems.

Perceptual brightness-based inverse tone mapping for high dynamic range imaging

Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we . present a new,LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.