Awesome
BibTeX
@INPROCEEDINGS{punnappurath2020modeling,
author={Abhijith Punnappurath and Abdullah Abuolaim and Mahmoud Afifi and Michael S. Brown},
booktitle={IEEE International Conference on Computational Photography (ICCP)},
title={Modeling Defocus-Disparity in Dual-Pixel Sensors},
year={2020}
}
How to run
- This is the code for the optimization-based approach described in Section 4.1 of our paper. The implementation is in Matlab.
- The post-process edge-aware filtering described in Section 4.3 consists of a bilateral solver and a guided filter. Official implementations released by the authors have been used - the bilateral solver is in Python and the guided filter in Matlab.
- To obtain our final result, run Steps 1, 2, and 3 sequentially, where Step 1 is the main optimization, and Steps 2 and 3 are the post-process bilateral solver and guided filter, respectively.
- The data corresponding to Fig. 7 of our paper can be found here, and Figs. 1 and 8 can be found here.
- Running the code as is produces our result in Fig. 8(f) third column.
- Other outputs can be generated by appropriately setting the input image path here in Step 1, and here and here in Steps 2 and 3, respectively.
- The
img_name variable to use for Steps 2 and 3 will be displayed when Step 1 finishes execution.
- Note that the optimization-based approach is very slow since it requires minimizing our cost function of equation (7) at each window.
- Evaluation code can be found here
Dataset
- Download our dataset used for evaluation in Section 5.4 here.
- All results in Table 1 were reported on 16-bit uncompressed TIFF images. The dataset shared on the link above contains 8-bit JPEG images (for file size considerations). Results may vary slightly.
Video spotlight
- Watch the YouTube video here
Visualization of our parameterized dual-pixel kernel of equation 6
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