Geometric and colorimetric error compensation for multi-view images |
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| Affiliation: | 1. University of Science and Technology of China, No. 96, Jinzhai Road, Baohe District, Hefei, Anhui 230026, PR China;2. Microsoft Research Asia, No. 5 Danling Street, Haidian District, Beijing 100080, PR China;3. School of Information and Electronics, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, PR China;1. Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia;2. Interactive Systems – Department of Informatics, University of Sussex, Brighton, United Kingdom;1. Department of Rheumatology and Allergy, Xuanwu Hospital, Capital Medical University, Beijing, China;2. Department of Pediatrics and Communicable Diseases, The University of Michigan Medical School, Ann Arbor, MI, USA;3. Department of Human Genetics, The University of Michigan Medical School, Ann Arbor, MI, USA;1. School of Chemical Engineering, Ningbo University of Technology, Ningbo 315016, PR China;2. UNILAB, State Key Lab of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, PR China;3. Shanghai Huayi Group Co. Ltd, Shanghai 200431, PR China |
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| Abstract: | In general, excessive colorimetric and geometric errors in multi-view images induce visual fatigue to users. Various works have been proposed to reduce these errors, but conventional works have only been available for stereoscopic images while requiring cumbersome additional tasks, and often showing unstable results. In this paper, we propose an effective multi-view image refinement algorithm. The proposed algorithm analyzes such errors in multi-view images from sparse correspondences and compensates them automatically. While the conventional works transform every view to compensate geometric errors, the proposed method transforms only the source views with consideration of a reference view. Therefore this approach can be extended regardless of the number of views. In addition, we also employ uniform view intervals to provide consistent depth perception among views. We correct color inconsistency among views from the correspondences by considering importance and channel properties. Various experimental results show that the proposed algorithm outperforms conventional approaches and generates more visually comfortable multi-view images. |
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| Keywords: | Multi-view image Geometric compensation Color correction Uniform view interval Vertical disparity reduction Projective transformation Visual fatigue 3DTV |
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