用手机双摄融合去除屏幕摩尔纹，效果优于现有方法。
Image Demoiréing Using Dual Camera Fusion on Mobile Phones
- 利用超广角镜头辅助主摄去摩尔纹，借不同焦距差异互补信息。
- 在9000张真实场景数据上测试，显著提升大而重摩尔纹消除效果。
- 轻量级设计适合移动端部署，适合手机影像开发者参考。
拍摄电子屏幕时，图像常出现摩尔纹，严重影响画质。现有去摩尔纹方法在处理大而重的摩尔纹时面临挑战。为此，我们提出双摄融合去摩尔纹（DCID）方法，利用超广角（UW）图像辅助宽角（W）图像的去摩尔纹处理。该思路基于两点：（1）现代智能手机普遍配备双摄像头；（2）当宽角图像因焦距差异出现摩尔纹时，超广角图像通常仍能保留正常颜色与纹理。我们设计了一种高效DCID方法，将轻量级超广角图像编码器集成到现有去摩尔纹网络中，并提出一种快速两阶段图像对齐方式。此外，我们构建了一个大规模真实世界数据集，涵盖多种手机与显示器，共约9000个样本。实验表明，本方法在该数据集上优于当前最优方法。代码与数据集已开源。
原文摘要 · Abstract (English)
When shooting electronic screens, moiré patterns usually appear in captured images, which seriously affects the image quality. Existing image demoiréing methods face great challenges in removing large and heavy moiré. To address the issue, we propose to utilize Dual Camera fusion for Image Demoiréing (DCID), \ie, using the ultra-wide-angle (UW) image to assist the moiré removal of wide-angle (W) image. This is inspired by two motivations: (1) the two lenses are commonly equipped with modern smartphones, (2) the UW image generally can provide normal colors and textures when moiré exists in the W image mainly due to their different focal lengths. In particular, we propose an efficient DCID method, where a lightweight UW image encoder is integrated into an existing demoiréing network and a fast two-stage image alignment manner is present. Moreover, we construct a large-scale real-world dataset with diverse mobile phones and monitors, containing about 9,000 samples. Experiments on the dataset show our method performs better than state-of-the-art methods. Code and dataset are available at https://github.com/Mrduckk/DCID.
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