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Proceedings Paper

High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project
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Paper Abstract

Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

Paper Details

Date Published: 30 April 2015
PDF: 11 pages
Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 953417 (30 April 2015); doi: 10.1117/12.2182844
Show Author Affiliations
Pierre-Jean Lapray, Le2i, CNRS, Univ. de Bourgogne (France)
Barthélémy Heyrman, Le2i, CNRS, Univ. de Bourgogne (France)
Dominique Ginhac, Le2i, CNRS, Univ. de Bourgogne (France)

Published in SPIE Proceedings Vol. 9534:
Twelfth International Conference on Quality Control by Artificial Vision 2015
Fabrice Meriaudeau; Olivier Aubreton, Editor(s)

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