Adaptive High Dynamic Range for Time-of-Flight Cameras

Abstract

The limited dynamic range of conventional digital cameras is a well-known problem. A common solution is to apply high-dynamic-range (HDR) techniques over several images acquired using different exposure times. Time-of-flight (ToF) cameras using a photonic mixer device (PMD) are not an exception, since the dynamic range of its dual pixels is also limited. Furthermore, in this case, the saturation of the pixel channels leads to wrong depth measurements. An appropriate solution is the suppression of background illumination (SBI) system designed by the PMD. This system actually extends the dynamic range of the camera by hardware, but it also introduces noise when activated. In this paper, we present an adaptive HDR (AHDR) solution to the problem for the ToF case that overcomes the limited dynamic range of the system, allowing sensing along a theoretically infinite dynamic range with the only limitations of the power of the illumination system and the decay of the SNR with higher distances or lower illumination intensities. Our method is able to detect and segment relevant scene regions responsible for unexpected saturation, i.e., close foreground objects, from the rest of the scene and adjust the exposure times of the acquired images considering them. The results show a reduction in detail losses and a higher SNR in the AHDR raw images, with respect to single acquisitions. This results in a dramatic depth error reduction and effective axial resolution improvement in critical areas, while keeping a high frame rate. In addition, the SBI-related noise is eliminated.Index Terms-High dynamic range (HDR), noise reduction, photonic mixer device (PMD), suppression of background illumination (SBI), time-of-flight (ToF).

Multipath Interference Suppression in Time-of-Flight Sensors by Exploiting the Amplitude Envelope of the Transmission Signal

“…The systematic errors include the integration time (IT) error, amplitude ambiguity, temperature error, depth distortion error, and the built-in pixel error, and the non-systematic errors include MpI, background illumination, scattering noise, and motion blur [28], [29]. Modern ToF cameras use techniques such as the suppression of background illumination [30] or employ special background-light immune sensors to suppress the effect of ambient light in the measurements [31], [32]. Thus, the term in the above equation is neglected in the calculations in this paper.…”

HDR-TOF: HDR Time-of-Flight Imaging via Modulo Acquisition

“…With the widespread applications of 3D imaging in the areas of robotics, surveillance, remote sensing [10], scientific imaging and most importantly, autonomous navigation [11], reliability and stability issues necessitated the development of 3D HDR imaging solutions. While purely algorithmic solutions [12][13][14] are lack of guarantees for errorless recovery, other solutions based on advanced hardware design [15,16], are often complex and impractical for off-the-shelf products.…”

“…In this paper, we take a different approach to the 3D-HDR imaging based on time-of-flight sensors. Our approach is based on the Unlimited Sensing Framework (USF) [17][18][19][20][21][22][23][24][25], that unlike algorithms-only [12][13][14] or hardware-only [15,16] solutions, leverages a co-design of hardware and algorithms. In the USF, the signal's acquisition process utilizes the centered modulo operation defined by,…”