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Developing and integrating advanced image sensors with novel algorithms incamera systems are prevalent with the increasing demand for computationalphotography and imaging on mobile platforms. However, the lack of high-qualitydata for research and the rare opportunity for in-depth exchange of views fromindustry and academia constrain the development of mobile intelligentphotography and imaging (MIPI). To bridge the gap, we introduce the first MIPIchallenge including five tracks focusing on novel image sensors and imagingalgorithms. In this paper, RGBW Joint Remosaic and Denoise, one of the fivetracks, 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 pairs. Inaddition, for each scene, RGBW of different noise levels was provided at 0dB,24dB, and 42dB. All the data were captured using an RGBW sensor in both outdoorand indoor conditions. The final results are evaluated using objective metricsincluding PSNR, SSIM, LPIPS, and KLD. A detailed description of all modelsdeveloped in this challenge is provided in this paper. More details of thischallenge and the link to the dataset can be found athttps://github.com/mipi-challenge/MIPI2022.

MIPI 2022 Challenge on RGBW Sensor Re-mosaic: Dataset and Report