MIPI 2022 Challenge on RGBW Sensor Re-Mosaic: Dataset and Report
Abstract
Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, RGBW Joint Remosaic and Denoise, one of the five tracks, working on the interpolation of RGBW CFA to Bayer at full-resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality RGBW and Bayer pair. In addition, for each scene, RGBW of different noise level were provided at 0 dB, 24 dB and 42 dB. All the data were captured using a RGBW sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [ 5 ], LPIPS [ 7 ] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022 .
Cite
Text
Yang et al. "MIPI 2022 Challenge on RGBW Sensor Re-Mosaic: Dataset and Report." European Conference on Computer Vision Workshops, 2022. doi:10.1007/978-3-031-25072-9_3Markdown
[Yang et al. "MIPI 2022 Challenge on RGBW Sensor Re-Mosaic: Dataset and Report." European Conference on Computer Vision Workshops, 2022.](https://mlanthology.org/eccvw/2022/yang2022eccvw-mipi/) doi:10.1007/978-3-031-25072-9_3BibTeX
@inproceedings{yang2022eccvw-mipi,
title = {{MIPI 2022 Challenge on RGBW Sensor Re-Mosaic: Dataset and Report}},
author = {Yang, Qingyu and Yang, Guang and Jiang, Jun and Li, Chongyi and Feng, Ruicheng and Zhou, Shangchen and Sun, Wenxiu and Zhu, Qingpeng and Loy, Chen Change and Gu, Jinwei and Sun, Lingchen and Wu, Rongyuan and Yi, Qiaosi and Xu, Rongjian and Liu, Xiaohui and Zhang, Zhilu and Wu, Xiaohe and Wang, Ruohao and Li, Junyi and Zuo, Wangmeng and Fang, Faming},
booktitle = {European Conference on Computer Vision Workshops},
year = {2022},
pages = {36-45},
doi = {10.1007/978-3-031-25072-9_3},
url = {https://mlanthology.org/eccvw/2022/yang2022eccvw-mipi/}
}