Developing and integrating advanced image sensors with novel algorithms in camera systems are 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 an in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). With the success of the 1st MIPI Workshop@ECCV 2022, we introduce the second MIPI challenge, including four tracks focusing on novel image sensors and imaging algorithms. This paper summarizes and reviews the RGBW Joint Remosaic and Denoise track on MIPI 2023. In total, 81 participants were successfully registered, and 4 teams submitted results in the final testing phase. The final results are evaluated using objective metrics, including PSNR, SSIM, LPIPS, and KLD. A detailed description of the top three models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://mipi-challenge.org/MIPI2023/.
翻译:随着对移动平台计算摄影和成像的需求不断增加,开发和集成先进的图像传感器与新颖算法的相机系统变得日益普及。然而,缺乏用于研究的高质量数据以及行业和学术交流的难得机会制约着移动智能摄影和成像 (MIPI) 的发展。随着第一次 MIPI 工作坊 @ ECCV 2022 的成功举办,我们推出了第二次 MIPI 挑战赛,包括四个赛道,重点关注新型图像传感器和成像算法。本文总结和回顾了 MIPI 2023 中关于 RGBW Joint Remosaic 和 Denoise 赛道的情况。共有 81 名参赛者成功注册,4 支团队在最后的测试阶段提交了结果。最终结果使用 PSNR、SSIM、LPIPS 和 KLD 等客观评估指标进行评估。本文提供了本次挑战赛中排名前三的模型的详细描述。有关此挑战赛的更多详细信息以及数据集链接,请访问 https://mipi-challenge.org/MIPI2023/。