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IMPROVING DISPARITY MAP ESTIMATION FOR MULTI-VIEW NOISY IMAGES
![](https://sigport.org/sites/default/files/styles/home/public/ICASSP_2018_docs.jpg?itok=gxiDHw0M)
- Citation Author(s):
- Submitted by:
- Yu Hen Hu
- Last updated:
- 12 April 2018 - 12:44pm
- Document Type:
- Poster
- Document Year:
- 2018
- Event:
- Presenters:
- Yu Hen Hu
- Paper Code:
- 3720
- Categories:
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A robust multi-view disparity estimation algorithm for noisy images is presented. The proposed algorithm constructs 3D focus image stacks (3DFIS) by projecting and stacking multi-view images and estimates a disparity map based on the 3DFIS. To make the algorithm robust to noise and occlusion, a texture-based view selection and patch size variation scheme based on texture map is proposed. Experiment results indicate that the proposed algorithm outperforms conventional stereo matching algorithms as well as previously reported multi-view disparity estimation algorithms under noisy conditions.