Rendering non-pictorial (Scientific) high dynamic range images

In recent years, the graphics community is seeing an increasing demand for the capture and usage of high-dynamic-range (HDR) images. Since the production of HDR imagery is not solely the domain of the visualization of real life or computer generated scenes, novel techniques are also required for imagery captured from non-visual sources such as remote sensing, medical imaging, astronomical imaging, etc. This research proposes to integrate the techniques used for the display of high-dynamic-range pictorial imagery for the practical visualization of non-pictorial (scientific) imagery for data mining and interpretation. Nine algorithms were utilized to overcome the problem associated with rendering the high-dynamic-range image data to low-dynamic-range display devices, and the results were evaluated using a psychophysical experiment. Two paired-comparison experiments and a target detection experiment were performed. Paired-comparison results indicate that the Zone System performs the best on average and the Local Color Correction method performs the worst. The results show that the performance of different encoding schemes depend on the type of data being visualized. The correlation between the preference and scientific usefulness judgments (R2 = 0.31) demonstrates that observers tend to use different criteria when judging the scientific usefulness versus image preference. The experiment was conducted using observers with expertise (Radiologists) for the Medical image to further elucidate the success of HDR rendering on these data. The results indicated that both Radiologists and Non-radiologists tend to use similar criteria regardless of their experience and expertise when judging the usefulness of rendered images. A target detection experiment was conducted to measure the detectability of an embedded noise target in the Medical image to demonstrate the effect of the tone mapping operators on target detection. The result of the target detection experiment illustrated that the detectability of targets the image is greatly influenced by the rendering algorithm due to the inherent differences in tone mapping among the algorithms

Objective and subjective assessment of perceptual factors in HDR content processing

The development of the display and camera technology makes high dynamic range (HDR) image become more and more popular. High dynamic range image give us pleasant image which has more details that makes high dynamic range image has good quality. This paper shows us the some important techniques in HDR images. And it also presents the work the author did. The paper is formed of three parts. The first part is an introduction of HDR image. From this part we can know why HDR image has good quality

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

Põhjalik uuring ülisuure dünaamilise ulatusega piltide toonivastendamisest koos subjektiivsete testidega

A high dynamic range (HDR) image has a very wide range of luminance levels that traditional low dynamic range (LDR) displays cannot visualize. For this reason, HDR images are usually transformed to 8-bit representations, so that the alpha channel for each pixel is used as an exponent value, sometimes referred to as exponential notation [43]. Tone mapping operators (TMOs) are used to transform high dynamic range to low dynamic range domain by compressing pixels so that traditional LDR display can visualize them. The purpose of this thesis is to identify and analyse differences and similarities between the wide range of tone mapping operators that are available in the literature. Each TMO has been analyzed using subjective studies considering different conditions, which include environment, luminance, and colour. Also, several inverse tone mapping operators, HDR mappings with exposure fusion, histogram adjustment, and retinex have been analysed in this study. 19 different TMOs have been examined using a variety of HDR images. Mean opinion score (MOS) is calculated on those selected TMOs by asking the opinion of 25 independent people considering candidates’ age, vision, and colour blindness

A Model of Local Adaptation

The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility(detection) thresholds in complex images.We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping

Compression, Modeling, and Real-Time Rendering of Realistic Materials and Objects

The realism of a scene basically depends on the quality of the geometry, the illumination and the materials that are used. Whereas many sources for the creation of three-dimensional geometry exist and numerous algorithms for the approximation of global illumination were presented, the acquisition and rendering of realistic materials remains a challenging problem. Realistic materials are very important in computer graphics, because they describe the reflectance properties of surfaces, which are based on the interaction of light and matter. In the real world, an enormous diversity of materials can be found, comprising very different properties. One important objective in computer graphics is to understand these processes, to formalize them and to finally simulate them. For this purpose various analytical models do already exist, but their parameterization remains difficult as the number of parameters is usually very high. Also, they fail for very complex materials that occur in the real world. Measured materials, on the other hand, are prone to long acquisition time and to huge input data size. Although very efficient statistical compression algorithms were presented, most of them do not allow for editability, such as altering the diffuse color or mesostructure. In this thesis, a material representation is introduced that makes it possible to edit these features. This makes it possible to re-use the acquisition results in order to easily and quickly create deviations of the original material. These deviations may be subtle, but also substantial, allowing for a wide spectrum of material appearances. The approach presented in this thesis is not based on compression, but on a decomposition of the surface into several materials with different reflection properties. Based on a microfacette model, the light-matter interaction is represented by a function that can be stored in an ordinary two-dimensional texture. Additionally, depth information, local rotations, and the diffuse color are stored in these textures. As a result of the decomposition, some of the original information is inevitably lost, therefore an algorithm for the efficient simulation of subsurface scattering is presented as well. Another contribution of this work is a novel perception-based simplification metric that includes the material of an object. This metric comprises features of the human visual system, for example trichromatic color perception or reduced resolution. The proposed metric allows for a more aggressive simplification in regions where geometric metrics do not simplif

Relating Standardized Visual Perception Measures to Simulator Visual System Performance

Human vision is quantified through the use of standardized clinical vision measurements. These measurements typically include visual acuity (near and far), contrast sensitivity, color vision, stereopsis (a.k.a. stereo acuity), and visual field periphery. Simulator visual system performance is specified in terms such as brightness, contrast, color depth, color gamut, gamma, resolution, and field-of-view. How do these simulator performance characteristics relate to the perceptual experience of the pilot in the simulator? In this paper, visual acuity and contrast sensitivity will be related to simulator visual system resolution, contrast, and dynamic range; similarly, color vision will be related to color depth/color gamut. Finally, we will consider how some characteristics of human vision not typically included in current clinical assessments could be used to better inform simulator requirements (e.g., relating dynamic characteristics of human vision to update rate and other temporal display characteristics)

Real-time Cinematic Design Of Visual Aspects In Computer-generated Images

Creation of visually-pleasing images has always been one of the main goals of computer graphics. Two important components are necessary to achieve this goal --- artists who design visual aspects of an image (such as materials or lighting) and sophisticated algorithms that render the image. Traditionally, rendering has been of greater interest to researchers, while the design part has always been deemed as secondary. This has led to many inefficiencies, as artists, in order to create a stunning image, are often forced to resort to the traditional, creativity-baring, pipelines consisting of repeated rendering and parameter tweaking. Our work shifts the attention away from the rendering problem and focuses on the design. We propose to combine non-physical editing with real-time feedback and provide artists with efficient ways of designing complex visual aspects such as global illumination or all-frequency shadows. We conform to existing pipelines by inserting our editing components into existing stages, hereby making editing of visual aspects an inherent part of the design process. Many of the examples showed in this work have been, until now, extremely hard to achieve. The non-physical aspect of our work enables artists to express themselves in more creative ways, not limited by the physical parameters of current renderers. Real-time feedback allows artists to immediately see the effects of applied modifications and compatibility with existing workflows enables easy integration of our algorithms into production pipelines