Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments

© 2016 In this paper, we present a new technique for displaying High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays in an efficient way on the GPU. 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 the reference that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO. Finally, we present a GPU version, which is perceptually equal to the standard version but with much improved computational performance

Perceptually guided high-fidelity rendering exploiting movement bias in visual attention

A major obstacle for real-time rendering of high-fidelity graphics is computational complexity. A key point to consider in the pursuit of "realism in real time" in computer graphics is that the Human Visual System (HVS) is a fundamental part of the rendering pipeline. The human eye is only capable of sensing image detail in a 2 degrees foveal region, relying on rapid eye movements, or saccades, to jump between points of interest. These points of interest are prioritized based on the saliency of the objects in the scene or the task the user is performing. Such "glimpses" of a scene are then assembled by the HVS into a coherent, but inevitably imperfect, visual perception of the environment. In this process, much detail, that the HVS deems unimportant, may literally go unnoticed. Visual science research has identified that movement in the background of a scene may substantially influence how subjects perceive foreground objects. Furthermore, recent computer graphics work has shown that both fixed viewpoint and dynamic scenes can be selectively rendered without any perceptual loss of quality, in a significantly reduced time, by exploiting knowledge of any high-saliency movement that may be present. A high-saliency movement can be generated in a scene if an otherwise static objects starts moving. In this article, we investigate, through psychophysical experiments, including eye-tracking, the perception of rendering quality in dynamic complex scenes based on the introduction of a moving object in a scene. Two types of object movement are investigated: (i) rotation in place and (ii) rotation combined with translation. These were chosen as the simplest movement types. Future studies may include movement with varied acceleration. The object's geometry and location in the scene are not salient. We then use this information to guide our high-fidelity selective renderer to produce perceptually high-quality images at significantly reduced computation times. We also show how these results can have important implications for virtual environment and computer games applications

Investigation of the beat rate effect on frame rate for animated content

Knowledge of the Human Visual System (HVS) may be exploited in computer graphics to significantly reduce rendering times without the viewer being aware of any resultant image quality difference. Furthermore, cross-modal effects, that is the influence of one sensory input on another, for example sound and visuals, have also recently been shown to have a substantial impact on viewer perception of image quality. In this paper we investigate the relationship between audio beat rate and video frame rate in order to manipulate temporal visual perception. This represents an initial step towards establishing a comprehensive understanding for the audio-visual integration in multisensory environments

Dynamic range compression by differential zone mapping based on psychophysical experiments

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

A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images

An integrated gamut- and tone-management framework for color-accurate reproduction of high dynamic range images can prevent hue and luminance shifts while taking gamut boundaries into consideration. The proposed approach is conceptually and computationally simple, parameter-free, and compatible with existing tone-mapping operators