Multi-Exposure Decomposition-Fusion Model for High Dynamic Range Image Saliency Detection
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Pages (from-to) | 4409-4420 |
Number of pages | 12 |
Journal / Publication | IEEE Transactions on Circuits and Systems for Video Technology |
Volume | 30 |
Issue number | 12 |
Online published | 3 Apr 2020 |
Publication status | Published - Dec 2020 |
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Abstract
High dynamic range (HDR) imaging techniques have witnessed a great improvement in the past few decades. However, saliency detection task on HDR content is still far from well explored. In this paper, we introduce a multi-exposure decomposition-fusion model for HDR image saliency detection inspired by the brightness adaption mechanism. The proposed model is composed of three modules. Firstly, a decomposition module converts the input raw HDR image into a stack of LDR images by uniformly sampling the exposure time range. Secondly, a saliency region proposal network is employed to generate the candidate saliency maps for each LDR image in the exposure stack. Finally, an uncertainty weighting based fusion algorithm is applied to generate the overall saliency map for the input HDR image by merging the obtained LDR saliency maps. Extensive experiments show that our proposed model achieves superior performance compared with the state-of-theart methods on the existing HDR eye fixation databases. The source code of the proposed model are made publicly available at https://github.com/sunnycia/DFHSal.
Research Area(s)
- High dynamic range, brightness adaptation, image saliency detection, deep learning
Citation Format(s)
Multi-Exposure Decomposition-Fusion Model for High Dynamic Range Image Saliency Detection. / Wang, Xu; Sun, Zhenhao; Zhang, Qiudan et al.
In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 30, No. 12, 12.2020, p. 4409-4420.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review