AIM 2019 Challenge on RAW to RGB Mapping: Methods and Results
Citations Over TimeTop 10% of 2019 papers
Abstract
This paper reviews the first AIM challenge on mapping camera RAW to RGB images with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map the original low-quality RAW images from the Huawei P20 device to the same photos captured with the Canon 5D DSLR camera. The considered problem embraced a number of computer vision subtasks, such as image demosaicing, denoising, gamma correction, image resolution and sharpness enhancement, 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 baseline results, defining the state-of-the-art for RAW to RGB image restoration.
Related Papers
- → Color filter arrays: design and performance analysis(2005)255 cited
- → Universal demosaicking for imaging pipelines with an RGB color filter array(2005)63 cited
- → Single-Sensor RGB and NIR Image Acquisition: Toward Optimal Performance by Taking Account of CFA Pattern, Demosaicking, and Color Correction(2016)30 cited
- → Learning based demosaicing and color correction for RGB-IR patterned image sensors(2019)6 cited
- → UDP – a New Universal Demosaicing Pipeline Algorithm for RGB Color Filter Arrays(2014)