Separating true range measurements from multi-path and scattering interference in commercial range cameras

TLDR

Time‑of‑flight range cameras capture 3‑D images, but multi‑path interference causes scene‑dependent range distortions that are difficult to correct with post‑processing. The study demonstrates an algorithm that separates strong and weak light returns on commercial Mesa Imaging SR‑4000 and Canesta XZ‑422 range cameras. By acquiring additional raw images and applying an optimization‑based decomposition before range decoding, the method isolates individual component returns for each pixel. The approach yields substantial accuracy gains, particularly in darker scene areas.

Abstract

Time-of-flight range cameras acquire a three-dimensional image of a scene simultaneously for all pixels from a single viewing location. Attempts to use range cameras for metrology applications have been hampered by the multi-path problem, which causes range distortions when stray light interferes with the range measurement in a given pixel. Correcting multi-path distortions by post-processing the three-dimensional measurement data has been investigated, but enjoys limited success because the interference is highly scene dependent. An alternative approach based on separating the strongest and weaker sources of light returned to each pixel, prior to range decoding, is more successful, but has only been demonstrated on custom built range cameras, and has not been suitable for general metrology applications. In this paper we demonstrate an algorithm applied to both the Mesa Imaging SR-4000 and Canesta Inc. XZ-422 Demonstrator unmodified off-the-shelf range cameras. Additional raw images are acquired and processed using an optimization approach, rather than relying on the processing provided by the manufacturer, to determine the individual component returns in each pixel. Substantial improvements in accuracy are observed, especially in the darker regions of the scene.