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

Area of Science:

• Optics and Photonics
• Image Processing

Background:

• Compressive time-of-flight (ToF) imaging offers potential for cost-effective super-resolution (SR).
• Existing methods face challenges with efficiency and data storage, limiting practical application.

Purpose of the Study:

• To propose a fast and lightweight compressive ToF framework for SR.
• To address the limitations of current compressive ToF techniques in terms of efficiency and storage.

Main Methods:

• Introduction of a block compressed sensing method into SR image acquisition and data transmission.
• Development and experimental verification of a prototype system based on the proposed framework.

Main Results:

• Significantly decreased reconstruction time compared to existing compressive ToF systems.
• Substantially reduced data storage requirements.

Conclusions:

• The proposed framework offers a development direction for compressive ToF imaging.
• Provides guidance for researchers aiming for highly efficient and lightweight SR image reconstruction.