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Real-Time Interference Artifacts Suppression in Array of ToF Sensors.

Jozef Volak¹, Jakub Bajzik¹, Silvia Janisova¹

¹Department of Mechatronics and Electronics, University of Žilina, 010 26 Žilina, Slovakia.

Sensors (Basel, Switzerland)

|July 8, 2020

Summary

This study introduces a new Importance Map Based Median filtration algorithm to reduce interference artifacts in Time of Flight (ToF) sensor data. The method effectively suppresses noise from multi-camera interference, improving 3D depth perception.

Keywords:

3D imaging depth sensors interference suppression multi-camera interference

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Area of Science:

Computer Vision
Sensor Technology
Signal Processing

Background:

Time of Flight (ToF) sensors are susceptible to interference artifacts, particularly the multi-camera interference, due to their parallel scanning nature.
These artifacts degrade the accuracy of 3D depth data, impacting applications relying on precise spatial information.

Purpose of the Study:

To present a novel Importance Map Based Median filtration algorithm for suppressing multi-camera interference artifacts in ToF sensor data.
To evaluate the algorithm's effectiveness as a 3D filtration method for depth frame processing.

Main Methods:

The algorithm processes multiple depth frames by extracting interference regions.
It utilizes interpolation techniques within the identified interference areas to correct erroneous depth values.
The proposed method involves combining the Importance Map Based Median filtration with established filtering techniques.

Main Results:

The Importance Map Based Median filtration algorithm demonstrated significant suppression of interference artifacts.
Performance evaluation on real-world objects showed competitive or superior results compared to popular neural network and statistical filtering methods.
The algorithm proved effective across objects with varying textures and morphologies.

Conclusions:

The Importance Map Based Median filtration algorithm is a viable and effective method for mitigating multi-camera interference in ToF sensors.
Its ability to process multiple depth frames and interpolate corrected data offers a robust solution for improving 3D depth sensing accuracy.
Further research could explore combining this method with other advanced filtering techniques for enhanced performance.