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CG-TMO: A Local Tone Mapping for Computer Graphics Generated Content
Abstract and Figures
Physically based renderers produce high quality images with high dynamic range (HDR) values. Therefore, these images need to be tone mapped in order to be displayed on low dynamic range (LDR) displays. A typical approach is to blindly apply tone mapping operators without taking advantage of the extra information that comes for free from the modeling process for creating a 3D scene. In this paper, we propose a novel pipeline for tone mapping high dynamic range (HDR) images which are generated using physically based renderers. Our work exploits information of a 3D scene, such as geometry, materials, luminaries, etc. This allows to limit the assumptions that are typically made during the tone mapping step. As consequence of this, we will show improvements in term of quality while keeping the entire process straightforward.
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Tone Mapping of HDR Images has been studied extensively since the introduction of digital HDR capture methods. However, until recently HDR video has not been realized in a viable form as that given by Tocci et al.[1], which will lead to readily available HDR video cameras. Because they capture video with much broader dy-namic range than can currently be displayed, these cameras present a unique challenge. In order to maintain backward-compatibility with legacy broadcast, recording, and display equipment, HDR video cameras need to provide a real-time tonemapped LDR video stream without the benefit of post-processing steps. The purpose of this research is to present a complete TMO solution that can be imple-mented in real time hardware to yield a high-quality automated LDR video stream suitable for direct use by today's recording, broadcast, and display equipment.
High dynamic range (HDR) rendering is becom-ing an increasingly popular technique in computer graphics. Its challenge consists in mapping the resulting images' large range of intensities to the much narrower ones of the dis-play devices in a way that preserves contrastive details. Lo-cal tone mapping operators effectively perform the required compression by adapting the luminance level of each pixel with respect to its local neighborhood. While they gener-ate significantly better results when compared to global op-erators, their computational costs are considerably higher, which has prevented their use in real-time applications. This paper presents a real-time technique for photographic lo-cal tone reproduction that runs entirely on the GPU and is significantly faster than existing implementations that pro-duce similar results. Our approach is based on the use of summed-area tables for accelerating the convolution of the local neighborhoods with a box filter and provides an at-tractive solution for HDR rendering applications that require high performance without compromising image quality.
When preparing high dynamic range images (HDR) for dis-
play on standard monitors, it is often necessary to make a
choice between global and local tone mapping. While the
former is simple and efficient, it may fail to reproduce details
in high contrast image regions. Although, the latter can better
reproduce details in such regions, it often comes at the cost
of increased complexity and computational time. In this pa-
per, we present an algorithm that combines the best of both
approaches. We perform local tone mapping only in high frequency image regions where the visibility of details can be an issue. In low frequency regions, we employ global tone
mapping to save computational resources without degrading
quality. Our algorithm is most suitable for tone mapping operators (TMOs) that utilize the concept of local adaptation luminances.
The subjective quality of a virtual world depends on the quality of displayed images. In the present paper, we address a technical aspect of image quality in virtual environments. Due to the recent development of high dynamic range (HDR) imaging in computer graphics applications, tone mapping operators (TMO) are needed in the graphic pipeline, and their impact on the final image quality needs to be tested. Previous evaluations of such operators have emphasized the fact that the specific merit of a given operator may depend on both the scene and the application. The dynamic behavior of tone mapping operators was not tested before, and we have designed two psychophysical experiments in order to assess the relevance of various TMO for a specific class of virtual worlds, outdoor scenes at night and an interactive application, to explore an outdoor virtual world at night. In a first experiment, 5 HDR video clips were tone-mapped using 8 operators from the literature, resulting in 40 videos. These 40 videos were presented to 14 subjects, which were asked to rate their realism. However, the subject’s evaluation was not a direct comparison with the HDR videos. In a second experiment, 9 HDR photographs of urban scenes at night were tone-mapped with the same 8 operators. The resulting 72 photographs were presented to 13 subjects, at the location where the photographs were taken. The subjects were asked to rate the realism of each tone-mapped image, displayed on a laptop, with respect to the physical scene they experienced. The first experiment emphasized the importance of modeling the temporal visual adaptation for a night-time application.
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.
Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a Structural Similarity Index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MatLab implementation of the proposed algorithm is available online at http://www.cns.nyu.edu/~lcv/ssim/.
Tone mapping is the process of mapping high dynamic range images to the low dynamic range of current displays. So far, tone mapping research was focused on static images, but with powerful graphics hardware available today, real time tone mapping becomes possible. In this paper we describe tone mapping within a VR environment. The tone mapping operator utilizes information about the user's line of sight obtained by a tracking system. Adaptation is optimized for the current view point and costly image operations are restricted to the central view field. Since all computations are completely performed by graphics hardware, we achieve interactive frame rates.
Color adaptation is a well known ability of the human visual system (HVS). Colors are perceived as constant even though the illuminant color changes. Indeed, the perceived color of a diffuse white sheet of paper is still white even though it is illuminated by a single orange tungsten light, whereas it is orange from a physical point of view. Unfortunately global illumination algorithms only focus on the physics aspects of light transport. The ouput of a global illuminantion engine is an image which has to undergo chromatic adaptation to recover the color as perceived by the HVS. In this paper, we propose a new color adaptation method well suited to global illumination. This method estimates the adaptation color by averaging the irradiance color arriving at the eye. Unlike other existing methods, our approach is not limited to the view frustrum, as it considers the illumination from all the scene. Experiments have shown that our method outperforms the state of the art methods.
In this work we present a new algorithm for accelerating the colour bilateral filter based on a subsampling strategy working in the spatial domain. The base idea is to use a suitable subset of samples of the entire kernel in order to obtain a good estimation of the exact filter values. The main advantages of the proposed approach are that it has an excellent trade-off between visual quality and speed-up, a very low memory overhead is required and it is straightforward to implement on the GPU allowing real-time filtering. We show different applications of the proposed filter, in particular efficient cross-bilateral filtering, real-time edge-aware image editing and fast video denoising. We compare our method against the state of the art in terms of image quality, time performance and memory usage. © 2012 Wiley Periodicals, Inc.