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The development of high dynamic range (HDR) imagery has brought us to the verge of arguably the largest change in image display technologies since the transition from black-and-white to color television. Novel capture and display hardware will soon enable consumers to enjoy the HDR experience in their own homes. The question remains, however, of what to do with existing images and movies, which are intrinsically low dynamic range (LDR). Can this enormous volume of legacy content also be displayed effectively on HDR displays? We have carried out a series of rigorous psychophysical investigations to determine how LDR images are best displayed on a state-of-the-art HDR monitor, and to identify which stages of the HDR imaging pipeline are perceptually most critical. Our main findings are: (1) As expected, HDR displays outperform LDR ones. (2) Surprisingly, HDR images that are tonemapped for display on standard monitors are often no better than the best single LDR exposure from a bracketed sequence. (3) Most importantly of all, LDR data does not necessarily require sophisticated treatment to produce a compelling HDR experience. Simply boosting the range of an LDR image linearly to fit the HDR display can equal or even surpass the appearance of a true HDR image. Thus the potentially tricky process of inverse tone mapping can be largely circumvented.

A series of three experiments has been performed to test both the preference and accuracy of HDR rendering algorithms in digital photography application. The goal was to develop a methodology for testing a wide-variety of previously published tone-mapping algorithms for overall preference and rendering accuracy. A number of algorithms were chosen and evaluated first in a paired-comparison experiment for overall image preference. A rating-scale experiment was then designed for further investigation of individual image-attributes that make up overall image preference. This was designed to identify the correlations between image attributes and the overall preference results obtained from the first experiments. In a third experiment, three real-world scenes with a diversity of dynamic range and spatial configuration were designed and captured to evaluate seven HDR rendering algorithms for both of their preference and accuracy performance by comparing the appearance of the physical scenes and the corresponding tonemapped images directly. In this series of experiments, a modified Durand & Dorsey’s bilateral filter technique consistently performed well for both preference and accuracy, suggesting that it a good candidate for a common algorithm that could be included in future HDR algorithm testing evaluations. The results of these experiments provide insight for understanding of perceptual HDR image rendering and should aid in design strategies for spatial processing and tone mapping. The results indicate ways to improve and design

We present a tone mapping algorithm that is derived from a model of retinal processing. Our approach has two major improvements over existing methods. First, tone mapping is applied directly on the mosaic image captured by the sensor, analogue to the human visual system that applies a non-linearity on the chromatic responses captured by the cone mosaic. This reduces the number of necessary operations by a factor three. Second, we introduce a variation of the center/surround class of local tone mapping algorithms, which are known to increase the local contrast of images but tend to create artifacts. Our method gives a good improvement in contrast while avoiding halos and maintaining good global appearance. Like traditional center/surround algorithms, our method uses a weighted average of surrounding pixel values. Instead of using it directly, the weighted average serves as a variable in the Naka-Rushton equation, which models the photoreceptors non-linearity. Our algorithm provides pleasing results on various images with different scene content and dynamic range.

The problem of reproducing high dynamic range images on devices with restricted dynamic range has gained a lot of interest in the computer graphics community. There exist various approaches to this issue, which span several research areas including computer graphics, image processing, color science, physiology, neurology, psychology, etc. These approaches assume a thorough knowledge of both the objective and subjective attributes of an image. However, no comprehensive overview and analysis of such attributes has been published so far. In this paper, we present an overview of image quality attributes of different tone mapping methods. Furthermore, we propose a scheme of relationships between these attributes, leading to the definition of an overall image quality measure. We present results of subjective psychophysical tests that we have performed to prove the proposed relationship scheme. We also present the evaluation of existing tone mapping methods with regard to these attributes. Our effort is not just useful to get into the tone mapping field or when implementing a tone mapping operator, but it also sets the stage for well-founded quality comparisons between tone mapping operators. By providing good definitions of the different attributes, user-driven or fully automatic comparisons are made possible at all. 1

An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Many real-world scenes contain a dynamic range that exceeds conventional display technology by several orders of magnitude. Through the combination of several existing technologies, new high dynamic range displays, capable of reproducing a range of intensities much closer to that of real environments, have been constructed. These benefits come at the cost of more optically complex devices; involving two image modulators, controlled in unison, to display images. We present several methods of rendering images to this new class of devices for reproducing photometrically accurate images. We discuss the process of calibrating a display, matching the response of the device with our ideal model. We then derive series of methods for efficiently displaying images, optimized for different criteria and evaluate them in a perceptual framework.

In modern computer graphics applications, textures play an important role in conveying the appearance of real-world materials. But while surface appearance can often be effectively captured with a photograph, it is difficult to use example imagery to synthesize fully three-dimensional solid textures that are perceptually similar to their inputs. Specifically, this research focuses on human perception of 3D solid textures composed of aggregate particles in a binding matrix. Holding constant an established algorithm for approximating particle distributions, we examine the problem of estimating particle shape. We consider four methods for approximating plausible particle shapes—including two methods of our own contribution. We compare the performance of these methods under a variety of input conditions using automated, perceptually-motivated metrics as well as a psychophysical experiment. In the course of assessing the relative performance of the four algorithms, we also evaluate the reliability of the automated metrics in predicting the results of the experiment.

Texture fractalization is used in many existing approaches to ensure the temporal coherence of a stylized animation. This paper presents the results of a psychophysical user-study evaluating the relative distortion induced by a fractalization process of typical medium textures. We perform a ranking experiment, assess the agreement among the participants and study the criteria they used. Finally we show that the average co-occurrence error is an efficient quality predictor in this context.