# SRA: Fast Removal of General Multipath for ToF Sensors

arXiv: https://arxiv.org/abs/1403.5919 · HTML: https://mlsanity.com/paper/1403.5919/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2014.

## Built on by (most cited first, 10 of 10)

- [iToF2dToF: A Robust and Flexible Representation for Data-Driven Time-of-Flight Imaging](https://mlsanity.com/paper/2103.07087/) (2021)
- [CroMo: Cross-Modal Learning for Monocular Depth Estimation](https://mlsanity.com/paper/2203.12485/) (2022)
- [RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising](https://mlsanity.com/paper/2111.15513/) (2021)
- [Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Data](https://mlsanity.com/paper/2108.03649/) (2021)
- [Swept-Angle Synthetic Wavelength Interferometry](https://mlsanity.com/paper/2205.10655/) (2022)
- [Lightweight Deep Learning Architecture for MPI Correction and Transient Reconstruction](https://mlsanity.com/paper/2111.14396/) (2021)
- [Solutions to Deepfakes: Can Camera Hardware, Cryptography, and Deep Learning Verify Real Images?](https://mlsanity.com/paper/2407.04169/) (2024)
- [Noise-Coded Illumination for Forensic and Photometric Video Analysis](https://mlsanity.com/paper/2507.23002/) (2025)
- [Centimeter-Wave Free-Space Time-of-Flight Imaging](https://mlsanity.com/paper/2105.11606/) (2021)
- [MPI Planar Correction of Pulse Based ToF Cameras](https://mlsanity.com/paper/2312.12064/) (2023)

## Abstract (arXiv)

A major issue with Time of Flight sensors is the presence of multipath interference. We present Sparse Reflections Analysis (SRA), an algorithm for removing this interference which has two main advantages. First, it allows for very general forms of multipath, including interference with three or more paths, diffuse multipath resulting from Lambertian surfaces, and combinations thereof. SRA removes this general multipath with robust techniques based on L1 optimization. Second, due to a novel dimension reduction, we are able to produce a very fast version of SRA, which is able to run at frame rate. Experimental results on both synthetic data with ground truth, as well as real images of challenging scenes, validate the approach.