Abstract: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 … Show more
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.
A multi-object distance determination method can be achieved by 932 nm structured light with one camera as the data receiver. The structured light generated by a liquid crystal on silicon spatial light modulator (LCoS-SLM) facilitates dynamic image projection on targets. A series of moving light strip images were captured and collected for data analysis. This method lifted the limitation of single-object distance determination and the limitation of the angle requirement between the camera and the light source in the triangulation method. The average error of this method was approximately 3% in the range of 700 mm to 1900 mm away from LCoS-SLM without further optimization. It provides a potential compact design for indoor multi-object distance determination in the future.
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