Research on depth measurement calibration of light field camera based on Gaussian fitting

• Published in: Scientific reports Vol. 14; no. 1; p. 8774
• Main Author: Yang, Miao
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 16-04-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166; 639/624; Accuracy; Calibration; Cameras; Deep learning; Depth calibration; Depth resolution; Electrons; Gaussian fitting; Humanities and Social Sciences; Image processing; Image rendering; Light; Methods; multidisciplinary; Neural networks; Optimization; Principles; Science; Science (multidisciplinary); Sensors; Image rendering; Depth resolution; Gaussian fitting; Depth calibration
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-59479-5

Optical field imaging technology does not require a complicated optical path layout and thus reduces hardware costs. Given that only one single exposure of a single camera can obtain three-dimensional information, this paper proposes an improved calibration method for depth measurement based on the theoretical model of optical field imaging. Specifically, the calibration time can be reduced since the Gaussian fitting can reduce the number of refocused images used to obtain the optimal refocusing coefficient calibration. Moreover, the proposed method achieves the same effect as the multiple refocusing calibration strategy but requires less image processing time during calibration. At the same time, this method's depth resolution is analyzed in detail.