Fast lightweight framework for time-of-flight super-resolution based on block compressed sensing

Abstract

Compressive time-of-flight (ToF) imaging for super-resolution (SR) has tremendous development potential owing to its cost-effectiveness and simplicity. However, existing compressive ToF methods are difficult to apply in practical situations because of their low efficiency and high data storage requirements. In this paper, we propose a fast and lightweight compressive ToF framework for SR. The block compressed sensing method, which shows distinct characteristics of high efficiency and low implementation cost, is introduced into the SR image acquisition and data transmission processes. Based on this framework, we establish a prototype system and verify it experimentally. Compared with existing compressive ToF systems, both the reconstruction time and data storage requirements are significantly decreased. We believe that this study provides a development direction for compressive ToF imaging and effective guidance for researchers realizing highly efficient and lightweight SR image reconstruction.