We propose a novel method for capturing high-speed, high dynamic range video with a single low-speed camera using a coded sampling technique. Traditional video cameras use a constant full-frame exposure time, which makes temporal super-resolution difficult due to the ill-posed nature of inverting the sampling operation. Our method samples at the same rate as the traditional low-speed camera but uses random per-pixel exposure times and offsets. By exploiting temporal and spatial redundancy in the video, we can reconstruct a high-speed video from the coded input. Furthermore, the different exposure times used in our sampling scheme enable us to obtain a higher dynamic range than a traditional camera or other temporal superresolution methods. We validate our approach using simulation and provide a detailed discussion on how to make a hardware implementation. In particular, we believe that our approach can maintain a 100% light throughput similarly to existing cameras and can be implemented on a single chip, making it suitable for small form factors.

This paper extends the classical warping-based optical flow method to achieve accurate flow in the presence of spatially-varying motion blur. Our idea is to parameterize the appearance of each frame as a function of both the pixel motion and the motion-induced blur. We search for the flows that best match two consecutive frames, which amounts to finding the derivative of a blurred frame with respect to both the motion and the blur, where the blur itself is a function of the motion. We propose an efficient technique to calculate the derivatives using prefiltering. Our technique avoids performing spatially-varying filtering (which can be computationally expensive) during the optimization iterations. In the end, our derivative calculation technique can be easily incorporated with classical flow code to handle video with non-uniform motion blur with little performance penalty. Our method is evaluated on both synthetic and real videos and outperforms conventional flow methods in the presence of motion blur.