Publication: Improved radiometric calibration by brightness transfer function based noise & outlier removal and weighted least square minimization
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Issued Date
2018
Resource Type
File Type
application/pdf
ISSN
9168532
Other identifier(s)
2-s2.0-85052023708
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
IEICE Transactions on Information and Systems. Vol E101D, No.8 (2018), p.2101-2114
Suggested Citation
Techawatcharapaikul C., Mittrapiyanuruk P., Kaewtrakulpong P., Siddhichai S., Chiracharit W. Improved radiometric calibration by brightness transfer function based noise & outlier removal and weighted least square minimization. IEICE Transactions on Information and Systems. Vol E101D, No.8 (2018), p.2101-2114. doi:10.1587/transinf.2017EDP7380 Retrieved from: https://hdl.handle.net/20.500.14740/4479
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.