Vast majority of digital images and video material stored today can capture only a fraction of visual information visible to the human eye and does not offer sufficient quality to fully exploit capabilities of new display devices. High dynamic range (HDR) image and video formats encode the full visible range of luminance and color gamut, thus offering ultimate fidelity, limited only by the capabilities of the human eye and not by any existing technology. In this paper we demonstrate how existing image and video compression standards can be extended to encode HDR content efficiently. This is achieved by a custom color space for encoding HDR pixel values that is derived from the visual performance data. We also demonstrate how HDR image and video compression can be designed so that it is backward compatible with existing formats.

Both High Dynamic Range images and their tone mapped correspondents contain relative luminance values which have to be mapped on a scale of available gray levels of a display. Such mapping includes brightness adjustment, which has a direct impact on the final image appearance and the observers' assessment of image quality. We conduct a psychophysical experiment in which subjects adjust image brightness to match their preference. We observe that the brightness choice is consistent across subjects and is primarily affected by image content. We investigate popular methods for automatic brightness adjustment and show a significant inaccuracy for a group of images. The incorrect brightness adjustment degrades in these cases perceived image quality. We identify characteristics of images that are highly correlated with the subjects' choice of brightness and develop an improved model for the brightness adjustment.

Abstract The ABSTRACT is to be in fully‐justified italicized text, between two horizontal lines, in one‐column format, below the author and affiliation information. Use the word “Abstract” as the title, in 9‐point Times, boldface type, left‐aligned to the text, initially capitalized. The abstract is to be in 9‐point, single‐spaced type. The abstract may be up to 3 inches (7.62 cm) long. Leave one blank line after the abstract, then add the subject categories according to the ACM Classification Index (see http://www.acm.org/class/1998/ ).

Abstract High Dynamic Range (HDR) images capture the full range of luminance present in real world scenes, and unlike Low Dynamic Range (LDR) images, can simultaneously contain detailed information in the deepest of shadows and the brightest of light sources. For display or aesthetic purposes, it is often necessary to perform tone mapping, which creates LDR depictions of HDR images at the cost of contrast information loss. The purpose of this work is two‐fold: to analyze a displayed LDR image against its original HDR counterpart in terms of perceived contrast distortion, and to enhance the LDR depiction with perceptually driven colour adjustments to restore the original HDR contrast information. For analysis, we present a novel algorithm for the characterization of tone mapping distortion in terms of observed loss of global contrast, and loss of contour and texture details. We classify existing tone mapping operators accordingly. We measure both distortions with perceptual metrics that enable the automatic and meaningful enhancement of LDR depictions. For image enhancement, we identify artistic and photographic colour techniques from which we derive adjustments that create contrast with colour. The enhanced LDR image is an improved depiction of the original HDR image with restored contrast information. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation I.4.0 [Image Processing and Computer Vision]: GeneralImage processing software

We present an interactive system for fully dynamic scene lighting using captured high dynamic range (HDR) video environment maps. The key component of our system is an algorithm for efficient decomposition of HDR video environment map captured over hemisphere into a set of representative directional light sources, which can be used for the direct lighting computation with shadows using graphics hardware. The resulting lights exhibit good temporal coherence and their number can be adaptively changed to keep a constant framerate while good spatial distribution (stratification) properties are maintained. We can handle a large number of light sources with shadows using a novel technique which reduces the cost of BRDF-based shading and visibility computations. We demonstrate the use of our system in a mixed reality application in which real and synthetic objects are illuminated by consistent lighting at interactive framerates.

An anchoring theory of lightness perception comprehensively explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. We present a novel approach to tone mapping of high dynamic range (HDR) images which is inspired by the anchoring theory. The key concept of this method is the decomposition of an HDR image into areas (frameworks) of consistent luminance and the local calculation of the lightness values. The net lightness of an image is calculated via the merging of the frameworks proportionally to their strength. We stress out the importance of relating the luminance to a known brightness value (anchoring) and investigate the advantages of anchoring to the luminance value perceived as white. We validate the accuracy of the lightness reproduction in the presented algorithm by simulating a well known perception experiment. Our approach does not affect the local contrast and preserves the natural colors of an HDR image due to the linear handling of luminance.

Global illumination dramatically improves realistic appearance\nof rendered scenes, but usually it is neglected in VR systems\ndue to its high costs. In this work we present an efficient \nglobal illumination solution specifically tailored for those CAVE\napplications, which require an immediate response for dynamic light\nchanges and allow for free motion of the observer, but involve scenes\nwith static geometry. As an application example we choose\nthe car interior modeling under free driving conditions.\nWe illuminate the car using dynamically changing High Dynamic Range \n(HDR) environment maps and use the Precomputed Radiance Transfer (PRT) \nmethod for the global illumination computation. We\nleverage the PRT method to handle scenes with non-trivial topology\nrepresented by complex meshes. Also, we propose a hybrid of\nPRT and final gathering approach for high-quality rendering\nof objects with complex Bi-directional Reflectance Distribution\nFunction (BRDF). We use\nthis method for predictive rendering of the navigation LCD panel\nbased on its measured BRDF. Since the global illumination \ncomputation leads to HDR images we propose a tone mapping\nalgorithm tailored specifically for the CAVE. We employ \nhead tracking to identify the observed screen region\nand derive for it proper luminance adaptation conditions, \nwhich are then used for tone mapping on all walls in the CAVE.\nWe distribute our global illumination and tone mapping computation\non all CPUs and GPUs available in the\nCAVE, which enables us to achieve interactive performance\neven for the costly final gathering approach.

Due to rapid technological progress in high dynamic range (HDR) video capture and display, the efficient storage and transmission of such data is crucial for the completeness of any HDR imaging pipeline. We propose a new approach for inter-frame encoding of HDR video, which is embedded in the well-established MPEG-4 video compression standard. The key component of our technique is luminance quantization that is optimized for the contrast threshold perception in the human visual system. The quantization scheme requires only 10--11 bits to encode 12 orders of magnitude of visible luminance range and does not lead to perceivable contouring artifacts. Besides video encoding, the proposed quantization provides perceptually-optimized luminance sampling for fast implementation of any global tone mapping operator using a lookup table. To improve the quality of synthetic video sequences, we introduce a coding scheme for discrete cosine transform (DCT) blocks with high contrast. We demonstrate the capabilities of HDR video in a player, which enables decoding, tone mapping, and applying post-processing effects in real-time. The tone mapping algorithm as well as its parameters can be changed interactively while the video is playing. We can simulate post-processing effects such as glare, night vision, and motion blur, which appear very realistic due to the usage of HDR data.