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About 10,000 papers for “High dynamic range”

High Dynamic Range Imaging

Eiler, Jan · Johann Wolfgang Goethe-Universität · 2011

Die digitale Fotografie erlaubt bereits mit Kameras der Mittelklasse die Produktion von sehr guten Bildern. Nach wie vor erreichen diese Ergebnisse nach über 20 Jahren Digitalfotografie weder im Farb- noch im Kontrastumfang die Qualität der analogen Fotografie und der Wahrnehmung des menschlichen Auges. Die High Dynamic Range Fotografie versucht über Hard- und Software-Lösungen Bildqualitäten zu produzieren die eine deutliche Qualitätsverbesserung liefern. Die Anwendung der HDR-Fotografie wird hauptsächlich für Produkt-, Architektur und Landschafts-Fotografie eingesetzt. Unterschiedliche Verfahren, hier vor allem im Bereich Tonemapping dienen der Datenaufbereitung für die Postproduktion - für Druck und multimediale Darstellungen. Wie ist die Qualität definiert? Gibt es wissenschaftliche Parameter zur Beschreibung und Eingrenzung des Themas? Diese Abschlussarbeit untersucht den Stand der Wissenschaft und Technik in der HDR-Fotografie, speziell im Bereich der wenig beschriebenen "Porträt-Fotografie", analysiert und entwickelt Handlungsanweisungen für Fotografen/innen. Im praktische Teil werden sowohl Hard- als auch Software-Lösungen zur Beurteilung und Verbesserung der Bildqualitäten ermittelt.

Cited by 0Open access

High Dynamic Range Imaging

Rahul Kumar Chaurasiya, K.R. Ramakrishnan · 2013

While real scenes produce a wide range of brightness variations, current cameras use low dynamic range image detector that typically provide 256 levels of brightness data at each pixel. We propose methods to create High Dynamic Range images, the method to enhance the dynamic range of is based on capturing multiple exposure photographs of the scene. Even if there are few methods available for creating HDR images, HDR display technologies still lag behind. We present a tone mapping algorithm to display HDR images on Low Dynamic Range display devices. We also deal with histogram manipulation for painterly effect on output. Applications of HDR images are discussed in brief. An algorithm to create HDR images for still scenes in Color Filter Array (CFA) domain is proposed and successfully implemented.

Cited by 14

High dynamic range imaging

Paul Debevec, Erik Reinhard, Greg Ward et al. · Journal of International Crisis and Risk Communication Research · 2004

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.

Cited by 181Open access

high dynamic range display

Hamish Carr, Silvester Czanner (editors, Robert Wanat et al. · 2013

High dynamic range (HDR) displays capable of reproducing scenes of high luminance (exceeding 2,000 cd/m 2) and contrast (more than 10,000:1) are a useful tool for research on visual performace, image quality or colour appearance. In this paper we describe a projector-based HDR display, giving details on its hardware components and software for driving and calibrating the display. We report the colorimetric properties of the display: the colour reproduction accuracy, colour gamut and local contrast dependent on the size of displayed checkerboard pattern. To verify whether our display can produce local contrast inducing the colour that appears perfectly black to the observer, we conducted an experiment with human observers. Our results indicate that for the test pattern, the effective local contrast of our display (2500:1) is sufficient to produce perfectly black colour, which requires a contrast between 1300:1 and 2400:1. Categories and Subject Descriptors (according to ACM CCS): I.4.0 [Computer Graphics]: Image processing and computer vision—Image displays/Image processing software

Cited by 0

High Dynamic Range Imaging

Shoji Yamamoto · The Journal of The Institute of Image Information and Television Engineers · 2012

Cited by 0Open access

High Dynamic Range Imaging

Greg Ward · Color and Imaging Conference · 2001

The ultimate in color reproduction is a display that can produce arbitrary spectral content over a 300-800 nm range with 1 arc-minute resolution in a full spherical hologram. Although such displays will not be available until next year, we already have the means to calculate this information using physically-based rendering. We would therefore like to know: how may we represent the results of our calculation in a device-independent way, and how do we map this information onto the displays we currently own? In this paper, we give an example of how to calculate full spectral radiance at a point and convert it to a reasonably correct display color. We contrast this with the way computer graphics is usually done, and show where reproduction errors creep in. We then go on to explain reasonable short-cuts that save time and storage space without sacrificing accuracy, such as illuminant discounting and human gamut color encodings. Finally, we demonstrate a simple and efficient tone-mapping technique that matches display visibility to the original scene.

Cited by 11Open access