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http://hdl.handle.net/10397/105466
Title: | Multiview high dynamic range image synthesis using fuzzy broad learning system | Authors: | Guo, H Sheng, B Li, P Chen, CLP |
Issue Date: | May-2021 | Source: | IEEE transactions on cybernetics, May 2021, v. 51, no. 5, p. 2735-2747 | Abstract: | Compared with the normal low dynamic range (LDR) images, the high dynamic range (HDR) images provide more dynamic range and image details. Although the existing techniques for generating the HDR images have a good effect for static scenes, they usually produce artifacts on the HDR images for dynamic scenes. In recent years, some learning-based approaches are used to synthesize the HDR images and obtain good results. However, there are also many problems, including the deficiency of explaining and the time-consuming training process. In this article, we propose a novel approach to synthesize multiview HDR images through fuzzy broad learning system (FBLS). We use a set of multiview LDR images with different exposure as input and transfer corresponding Takagi-Sugeno (TS) fuzzy subsystems; then, the structure is expanded in a wide sense in the “enhancement groups” which transfer from the TS fuzzy rules with nonlinear transformation. After integrating fuzzy subsystems and enhancement groups with the trained-well weight, the HDR image is generated. In FBLS, applying the incremental learning algorithm and the pseudoinverse method to compute the weights can greatly reduce the training time. In addition, the fuzzy system has better interpretability. In the learning process, IF-THEN fuzzy rules can effectively help the model to detect the artifacts and reject them in the final HDR result. These advantages solve the problem of existing deep-learning methods. Furthermore, we set up a new dataset of multiview LDR images with corresponding HDR ground truth to train our system. Our experimental results show that our system can synthesize high-quality multiview HDR images, which has a higher training speed than other learning methods. | Keywords: | Fuzzy broad learning system (FBLS) High dynamic range (HDR) image Multiview synthesis |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on cybernetics | ISSN: | 2168-2267 | EISSN: | 2168-2275 | DOI: | 10.1109/TCYB.2019.2934823 | Rights: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication H. Guo, B. Sheng, P. Li and C. L. P. Chen, "Multiview High Dynamic Range Image Synthesis Using Fuzzy Broad Learning System," in IEEE Transactions on Cybernetics, vol. 51, no. 5, pp. 2735-2747, May 2021 is available at https://doi.org/10.1109/TCYB.2019.2934823. |
Appears in Collections: | Journal/Magazine Article |
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Li_Multiview_High_Dynamic.pdf | Pre-Published version | 30.69 MB | Adobe PDF | View/Open |
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