Improved radiometric calibration by brightness transfer function based noise & outlier removal and weighted least square minimization
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Author list: Techawatcharapaikul C., Mittrapiyanuruk P., Kaewtrakulpong P., Siddhichai S., Chiracharit W.
Publisher: Institute of Electronics, Information and Communication Engineers
Publication year: 2018
Journal: IEICE Transactions on Information and Systems (0916-8532)
Volume number: E101D
Issue number: 8
Start page: 2101
End page: 2114
Number of pages: 14
ISSN: 0916-8532
eISSN: 1745-1361
Languages: English-Great Britain (EN-GB)
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Abstract
An improved radiometric calibration algorithm by extending the Mitsunaga and Nayar least-square minimization based algorithm with two major ideas is presented. First, a noise & outlier removal procedure based on the analysis of brightness transfer function is included for improving the algorithm’s capability on handling noise and outlier in least-square estimation. Second, an alternative minimization formulation based on weighted least square is proposed to improve the weakness of least square minimization when dealing with biased distribution observations. The performance of the proposed algorithm with regards to two baseline algorithms is demonstrated, i.e. the classical least square based algorithm proposed by Mitsunaga and Nayar and the state-of-the-art rank minimization based algorithm proposed by Lee et al. From the results, the proposed algorithm outperforms both baseline algorithms on both the synthetic dataset and the dataset of real-world images. Copyright © 2018 The Institute of Electronics.
Keywords
Brightness transfer function, Camera response function, Noise & outlier rejection, Radiometric calibration, Weighted least square minimization
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