论文标题
AIM 2020挑战在学到的图像信号处理管道上
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
论文作者
论文摘要
本文回顾了第二个目标学习的ISP挑战，并提供了建议的解决方案和结果的描述。参与的团队正在求解现实世界中的RAW-RGB映射问题，目标是将Huawei P20设备捕获的原始低质量原始图像映射到使用佳能5D DSLR相机获得的相同照片。所考虑的任务包含了许多复杂的计算机视觉子任务，例如图像表演，降解，白色平衡，颜色和对比度校正，演示等。在此挑战中使用的目标指标合并了忠实得分（PSNR和SSIM），以及在用户研究中测量的解决方案的结果。所提出的解决方案可显着改善基线结果，定义了实用图像信号处理管道建模的最先进。
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to-RGB mapping problem, where to goal was to map the original low-quality RAW images captured by the Huawei P20 device to the same photos obtained with the Canon 5D DSLR camera. The considered task embraced a number of complex computer vision subtasks, such as image demosaicing, denoising, white balancing, color and contrast correction, demoireing, etc. The target metric used in this challenge combined fidelity scores (PSNR and SSIM) with solutions' perceptual results measured in a user study. The proposed solutions significantly improved the baseline results, defining the state-of-the-art for practical image signal processing pipeline modeling.
