Adaptive compressive sensing algorithm for video acquisition using a single-pixel camera

Abstract. We propose a method to acquire compressed measurements for efficient video reconstruction using a single-pixel camera. The method is suitable for implementation using a single-pixel detector, along with a digital micromirror device or other types of spatial light modulators. Conventional implementations of single-pixel cameras are able to spatially compress the signal, but the compressed measurements make it difficult to exploit temporal redundancies directly. Moreover, a single-pixel camera needs to make measurements in a sequential manner before the scene changes, making it inefficient for video imaging. We discuss a measurement scheme that exploits sparsity along the time axis for video imaging. After acquiring all measurements required for the first frame, measurements are acquired only from the areas that change in subsequent frames. We segment the first frame, detect the magnitude and direction of change for each segment, and acquire compressed measurements for the changing segments in the predicted direction. Next, we compare the reconstruction results for a few test sequences with existing techniques and demonstrate the practical utility of the scheme.