High dynamic range video reconstruction from a stereo camera setup |
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| Affiliation: | 1. Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander University Erlangen-Nuremberg, Cauerstr. 7, 91058 Erlangen, Germany;2. Fraunhofer Institute for Integrated Circuits, Electronic Imaging, Am Wolfsmantel 33, 91058 Erlangen, Germany;1. Division of Computer and Telecommunications Engineering, Yonsei University, Gangwon 220-710, Republic of Korea;2. Samsung Electronics Corporation, Gyeonggi 443-803, Republic of Korea;3. Department of Information and Communication Engineering, Hanbat National University, Daejeon 305-719, Republic of Korea;4. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA;1. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong;1. Instituto de Telecomunicacoes, Polo de Coimbra, 3030-290 Coimbra, Portugal;2. Polytechnic Institute of Tomar, EST, Tomar, Portugal;3. Polytechnic Institute of Leiria, ESTG, Leiria, Portugal;4. University of Coimbra, DEEC, Coimbra, Portugal;1. Laboratory of Photogrammetry, Department of Surveying, National Technical University of Athens, GR-15780 Athens, Greece;2. Laboratory of Photogrammetry, Department of Surveying, Technological Educational Institute of Athens, GR-12210 Athens, Greece |
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| Abstract: | To overcome the dynamic range limitations in images taken with regular consumer cameras, several methods exist for creating high dynamic range (HDR) content. Current low-budget solutions apply a temporal exposure bracketing which is not applicable for dynamic scenes or HDR video. In this article, a framework is presented that utilizes two cameras to realize a spatial exposure bracketing, for which the different exposures are distributed among the cameras. Such a setup allows for HDR images of dynamic scenes and HDR video due to its frame by frame operating principle, but faces challenges in the stereo matching and HDR generation steps. Therefore, the modules in this framework are selected to alleviate these challenges and to properly handle under- and oversaturated regions. In comparison to existing work, the camera response calculation is shifted to an offline process and a masking with a saturation map before the actual HDR generation is proposed. The first aspect enables the use of more complex camera setups with different sensors and provides robust camera responses. The second one makes sure that only necessary pixel values are used from the additional camera view, and thus, reduces errors in the final HDR image. The resulting HDR images are compared with the quality metric HDR-VDP-2 and numerical results are given for the first time. For the Middlebury test images, an average gain of 52 points on a 0-100 mean opinion score is achieved in comparison to temporal exposure bracketing with camera motion. Finally, HDR video results are provided. |
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| Keywords: | High dynamic range video Stereo camera setup Stereo matching |
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