Coded Acquisition of High Frame Rate Video

TL;DR

This paper introduces a multi-camera coded acquisition framework for high frame rate video that relaxes hardware constraints and employs sparse recovery techniques, enabling ultra-high speed imaging with improved resolution.

Contribution

It proposes a novel multi-camera coded acquisition method that uses random measurements and sparse recovery to enhance high frame rate video capture beyond traditional hardware limits.

Findings

Effective multi-camera coded acquisition techniques demonstrated.

Simulation and experimental results validate the approach.

Trade-offs between performance and hardware complexity analyzed.

Abstract

High frame video (HFV) is an important investigational tool in sciences, engineering and military. In ultra-high speed imaging, the obtainable temporal, spatial and spectral resolutions are limited by the sustainable throughput of in-camera mass memory, the lower bound of exposure time, and illumination conditions. In order to break these bottlenecks, we propose a new coded video acquisition framework that employs K > 2 conventional cameras, each of which makes random measurements of the 3D video signal in both temporal and spatial domains. For each of the K cameras, this multi-camera strategy greatly relaxes the stringent requirements in memory speed, shutter speed, and illumination strength. The recovery of HFV from these random measurements is posed and solved as a large scale l1 minimization problem by exploiting joint temporal and spatial sparsities of the 3D signal. Three coded video acquisition techniques of varied trade offs between performance and hardware complexity are developed: frame-wise coded acquisition, pixel-wise coded acquisition, and column-row-wise coded acquisition. The performances of these techniques are analyzed in relation to the sparsity of the underlying video signal. Simulations of these new HFV capture techniques are carried out and experimental results are reported.