A depth image calibration method and system of a TOF camera system

Abstract

The embodiment of the invention provides a depth image calibration method and system for a TOF camera system, and the method comprises the steps: obtaining a corresponding depth image according to anoriginal phase image collected by the time-of-flight TOF camera system; And respectively carrying out geometric correction, time domain noise reduction and spatial domain noise reduction processing, FPPN correction, Wiggling correction and temperature error compensation on the depth image to obtain a calibrated depth image. multi-aspect calibration is carried out on a depth image; geometric correction, time domain noise reduction and spatial domain noise reduction processing, FPPN correction, Wigning correction and temperature error compensation are carried out, errors introduced from multipleaspects are eliminated, a calibrated depth image is obtained, so that the measurement error is greatly reduced, the reliability of the finally obtained depth image is greatly enhanced, and the methodcan be further applied to various depth applications.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of 3D imaging, and more specifically, to a depth image calibration method and system for a TOF camera system. Background technique [0002] Binocular ranging, structured light and Time-of-Flight (TOF) are the three mainstream 3D imaging technologies today. Among them, TOF has been gradually applied due to its simple principle, simple and stable structure, and long measurement distance. Gesture recognition, 3D modeling, unmanned driving and machine vision and other fields. [0003] The working principle of TOF technology is: the TOF camera actively emits a modulated light source to the surface of the measured object, the modulated light is reflected by the object and then captured by the TOF camera, and the distance between the object and the camera is obtained by calculating the time difference or phase difference between the modulation light source and the capture period. depth / distan...

AI Technical Summary

Problems solved by technology

[0007] 3) Temperature drift: In CMOS photoelectric sensors, temperature rise will lead to higher heat-generated electron rate, and electron mobility will decrease with temperature rise, so temperature change will affect the accuracy of measuring distance

[0008] 4) Noise: The sensor will be affected by thermal noise, shot noise, readout noise, etc. during the working process, and there will be random noise between different frame images

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