Outdoor vision systems are vulnerale to atmospheric turbulences such as rain, fog, and haze.
I have been working on a number of topics and applications that are related to light field imaging. This page gives a brief overlook of these areas.
Clear Vision Through the Rain
- Jie Chen, Cheen-Hau Tan, Junhui Hou, Lap-Pui Chau, and He Li, '’Robust Video Content Alignment and Compensation for Rain Removal in a CNN Framework’’, accepted as spotlight (6.6%) on IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, 2018.
Edge-preserving rain removal for light field images based on RPCA
- Cheen-Hau Tan, J. Chen, and Lap-Pui Chau, '’Edge-preserving rain removal for light field images based on RPCA’’’ IEEE International Conference on Digital Signal Processing (DSP), pp. 1-5, London, UK, 2017.
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Cheen-Hau Tan, Jie Chen, and Lap-Pui Chau. '’Dynamic scene rain removal for moving cameras,’’ IEEE International Conference on Digital Signal Processing (DSP), pp. 372-376, Hongkong, China, 2014.
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J. Chen and Lap-Pui Chau, '’A Rain Pixel Recovery Algorithm for Videos With Highly Dynamic Scenes,’’ IEEE Transactions on Image Processing (IEEE TIP), vol. 23, no. 3, pp. 1097-1104, 2014.
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Jie Chen, and Lap-Pui Chau, '’Rain removal from dynamic scene based on motion segmentation,’’ IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2139-2142, Beijing, China, 2013.
Vision Enhancement through the Haze
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Jie Chen, and Lap-Pui Chau. '’Heavy Haze Removal in A Learning Framework,’’ IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1590-1593, Lisbon, Portugal, 2015.
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Jie Chen, and Lap-Pui Chau, '’An Enhanced Window-Variant Dark Channel Prior for Depth Estimation Using Single Foggy Image,’’ IEEE International Conference on Image Processing (ICIP), pp. 3508-3512, Melbourne, Australia, 2013.
