Compared to DSLR cameras, smartphone cameras have smaller sensors, which
limits their spatial resolution; smaller apertures, which limits their light
gathering ability; and smaller pixels, which reduces their signal-to noise
ratio. The use of color filter arrays (CFAs) requires demosaicing, which
further degrades resolution. In this paper, we supplant the use of traditional
demosaicing in single-frame and burst photography pipelines with a multiframe
super-resolution algorithm that creates a complete RGB image directly from a
burst of CFA raw images. We harness natural hand tremor, typical in handheld
photography, to acquire a burst of raw frames with small offsets. These frames
are then aligned and merged to form a single image with red, green, and blue
values at every pixel site. This approach, which includes no explicit
demosaicing step, serves to both increase image resolution and boost signal to
noise ratio. Our algorithm is robust to challenging scene conditions: local
motion, occlusion, or scene changes. It runs at 100 milliseconds per
12-megapixel RAW input burst frame on mass-produced mobile phones.
Specifically, the algorithm is the basis of the Super-Res Zoom feature, as well
as the default merge method in Night Sight mode (whether zooming or not) on
Google's flagship phone.

这篇论文中，我们使用多帧超分辨率算法直接从一连串的彩色滤波阵列原始图像中创建完整的 RGB 图像，以替代传统的单帧和连拍摄影流程中使用的去马赛克方法。该算法旨在提高图像分辨率和信噪比，支持多种场景条件，可以在短时间内运行。实际应用于手机的两个功能：Super-Res Zoom 和 Night Sight 模式。