Correlation-based time-of-flight (ToF) imaging enables a diverse range of applications for its high frame rate, high resolution and low cost. However, the non-uniformity of the sensor significantly affects the flat-field accuracy of the ToF imaging system. In this paper, we analyze the sources of the non-uniformity and propose a systematic non-uniformity correction (NUC) method. The method utilizes the amplitude image, which can directly reflect the non-uniformity characteristics of the ToF sensor, to conduct NUC. Based on the established NUC system, the effectiveness and feasibility of the proposed NUC method are verified. Compared with the traditional methods, the RMSE was significantly reduced, while the SNR and PSNR were effectively improved. We believe this study provides new insights into the understanding of noise in the correlation-based ToF imaging system, and also provides effective references for the NUC of the three-dimensional measuring instruments.

Indirect time-of-flight (ToF) imaging systems enable a broad array of applications owing to their high frame rate, strong durability, and low cost. However, the wiggling-related error caused by the harmonics in the emitted signal significantly affects the range accuracy of indirect ToF imaging systems. In this paper, we establish a mathematical model of the wiggling-related error and propose a wiggling-related error correction method for indirect ToF imaging systems. This method adds a delay measurement and utilizes raw intensity measurements to evaluate the system state based on an adaptive Kalman filter (AKF), which is easy to implement in most indirect ToF imaging systems. Simulation and experimental results show that the proposed method performed well in reducing the wiggling-related error and had good robustness in different integration times. Compared with the existing methods, the proposed method not only has better performance but also is easier to implement. We believe that this study provides effective guidance for researchers understanding the wiggling-related error and a potential direction for the accuracy improvement of indirect ToF imaging systems.

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.

No abstract