Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13232
ชื่อเรื่อง: Improved radiometric calibration by brightness transfer function based noise & outlier removal and weighted least square minimization
ผู้แต่ง: Techawatcharapaikul C.
Mittrapiyanuruk P.
Kaewtrakulpong P.
Siddhichai S.
Chiracharit W.
Keywords: Calibration
Luminance
Radiometry
Statistics
Brightness transfer functions
Camera response functions
Outlier rejection
Radiometric calibrations
Weighted least squares
Transfer functions
วันที่เผยแพร่: 2018
บทคัดย่อ: 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.
URI: https://ir.swu.ac.th/jspui/handle/123456789/13232
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052023708&doi=10.1587%2ftransinf.2017EDP7380&partnerID=40&md5=c5045af01cb9d6cc68055e3acd29e0be
ISSN: 9168532
Appears in Collections:Scopus 1983-2021

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