High-dynamic-range imaging

About: High-dynamic-range imaging is a research topic. Over the lifetime, 766 publications have been published within this topic receiving 22577 citations.

Robust patch-based hdr reconstruction of dynamic scenes

Abstract: High dynamic range (HDR) imaging from a set of sequential exposures is an easy way to capture high-quality images of static scenes, but suffers from artifacts for scenes with significant motion. In this paper, we propose a new approach to HDR reconstruction that draws information from all the exposures but is more robust to camera/scene motion than previous techniques. Our algorithm is based on a novel patch-based energy-minimization formulation that integrates alignment and reconstruction in a joint optimization through an equation we call the HDR image synthesis equation. This allows us to produce an HDR result that is aligned to one of the exposures yet contains information from all of them. We present results that show considerable improvement over previous approaches.

Estimation-theoretic approach to dynamic range enhancement using multiple exposures

Abstract: We present a new approach for improving the effective dynamic range of cameras by using multiple photographs of the same scene taken with different exposure times. Using this method enables the photographer to accurately capture scenes that contain high dynamic range by using a device with low dynamic range, which allows the capture of scenes that have both very bright and very dark regions. We approach the problem from a probabilistic standpoint, distinguishing it from the other methods reported in the literature on photographic dynamic range improvement. A new method is proposed for determining the camera's response function, which is an iterative procedure that need be done only once for a particular camera. With the response function known, high dynamic range images can be easily constructed by a weighted average of the input images. The particular form of weighting is controlled by the probabilistic formulation of the problem, and results in higher weight being assigned to pixels taken at longer exposure times. The advantages of this new weighting scheme are explained by com- parison with other methods in the literature. Experimental results are presented to demonstrate the utility of the algorithm. © 2003 SPIE

Advanced High Dynamic Range Imaging: Theory and Practice

Abstract: Imaging techniques seek to simulate the array of light that reaches our eyes to provide the illusion of sensing scenes directly. Both photography and computer graphics deal with the generation of images. Both disciplines have to cope with the high dynamic range in the energy of visible light that human eyes can sense. Traditionally photography and computer graphics took different approaches to the high dynamic range problem. Work over the last ten years though has unified these disciplines and created powerful new tools for the creation of complex, compelling and realistic images. This book provides a practical introduction to the emerging new discipline of high dynamic range imaging that combines photography and computer graphics. By providing detailed equations and code, the book gives the reader the tools needed to experiment with new techniques for creating compelling images. A supplemental website contains downloads and additional information.

High Dynamic Range Imaging.

Abstract: Current display devices can display only a limited range of contrast and colors, which is one of the main reasons that most image acquisition, processing, and display techniques use no more than eight bits per color channel. This course outlines recent advances in high-dynamic-range imaging, from capture to display, that remove this restriction, thereby enabling images to represent the color gamut and dynamic range of the original scene rather than the limited subspace imposed by current monitor technology. This hands-on course teaches how high-dynamic-range images can be captured, the file formats available to store them, and the algorithms required to prepare them for display on low-dynamic-range display devices. The trade-offs at each stage, from capture to display, are assessed, allowing attendees to make informed choices about data-capture techniques, file formats, and tone-reproduction operators. The course also covers recent advances in image-based lighting, in which HDR images can be used to illuminate CG objects and realistically integrate them into real-world scenes. Through practical examples taken from photography and the film industry, it shows the vast improvements in image fidelity afforded by high-dynamic-range imaging.

Artifact-free High Dynamic Range imaging

Abstract: The contrast in real world scenes is often beyond what consumer cameras can capture. For these situations, High Dynamic Range (HDR) images can be generated by taking multiple exposures of the same scene. When fusing information from different images, however, the slightest change in the scene can generate artifacts which dramatically limit the potential of this solution. We present a technique capable of dealing with a large amount of movement in the scene: we find, in all the available exposures, patches consistent with a reference image previously selected from the stack. We generate the HDR image by averaging the radiance estimates of all such regions and we compensate for camera calibration errors by removing potential seams. We show that our method works even in cases when many moving objects cover large regions of the scene.