SIFT-flow-based color correction for multi-view video |
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| Affiliation: | 1. School of Information Science and Engineering, Huaqiao University, Xiamen, China;2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;1. University of Jinan, School of Information Science and Engineering, Shandong Provincial Key Laboratory of Network-Based Intelligent Computing, Jinan 250022, China;2. Department of Embedded Systems Engineering, College of Information and Technology, Incheon National University, Incheon, South Korea;3. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi׳an 710071, China;1. Sharif University of Technology – Department of Mathematical Sciences P.O. Box 11155-9415, Tehran, Iran;2. Kharazmi University – Faculty of Mathematics and Computer Science P.O. Box 15719-14911, Tehran, Iran;1. Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, Berlin, Germany;2. Department of Mathematics, Technical University of Berlin, Germany;3. Department of Electrical Engineering, Technical University of Berlin, Germany;1. Nanjing University, School of Electronic Science and Engineering, No. 163, Xianlin Dadao, Nanjing 210046, China;2. Navy General Hospital, Beijing 100088, China |
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| Abstract: | During the multi-view video acquisition, color variation across the views tends to be incurred due to different camera positions, orientations, and local lighting conditions. Such color variation will inevitably deteriorate the performance of the follow-up multi-view video processing, such as multi-view video coding (MVC). To address this problem, an effective color correction algorithm, called the SIFT flow-based color correction (SFCC), is proposed in this paper. First, the SIFT-flow technique is used to establish point-to-point correspondences across all the views of the multi-view video. The average color is then computed based on those identified common corresponding points and used as the reference color. By minimizing the energy of the difference yielded between the color of those identified common corresponding points in each view with respect to the reference color, the color correction matrix for each view can be obtained and used to correct its color. Experimental results have shown that the proposed SFCC algorithm is able to effectively eliminate the color variation inherited in multi-view video. By further exploiting the developed SFCC algorithm as a pre-processing for the MVC, extensive simulation results have shown that the coding efficiency of the color-corrected multi-view video can be greatly improved (on average, 0.85 dB, 1.27 dB and 1.63 dB gain for Y, U, and V components, respectively), compared with that of the original multi-view video without color correction. |
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| Keywords: | Multi-view video Color variation Color correction SIFT flow MVC |
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