Multispectral imaging based on natural neighbor interpolation with rendering under various illuminations

Tzren-ru Chou, Chi Heng Hsieh

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

In this study, we constructed the multispectral imaging by the reconstruction of spectral reflectance. This reconstruction method was based on natural neighbor interpolation, abbreviated as NNI. The experiments focused on the feasibility of the reconstruction of reflectance spectra with multispectral images, and the experimental targets were divided into two types; paper packages, and portraits. The performance was evaluated in terms of root mean square error (RMSE), color difference (?E), and peak signal-tonoise ratio (PSNR). The experimental results showed that the proposed NNI reconstruction method was able to directly generate target spectra from sRGB channel values accurately. Furthermore, even after rendering under various illuminations, the average of color difference was still within an acceptable range.

原文英語
主出版物標題Proceedings of 2017 International Conference on Advances in Image Processing, ICAIP 2017
發行者Association for Computing Machinery
頁面45-49
頁數5
ISBN(電子)9781450352956
DOIs
出版狀態已發佈 - 2017 八月 25
事件2017 International Conference on Advances in Image Processing, ICAIP 2017 - Bangkok, 泰国
持續時間: 2017 八月 252017 八月 27

出版系列

名字ACM International Conference Proceeding Series
Part F131200

其他

其他2017 International Conference on Advances in Image Processing, ICAIP 2017
國家泰国
城市Bangkok
期間17/8/2517/8/27

    指紋

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

引用此

Chou, T., & Hsieh, C. H. (2017). Multispectral imaging based on natural neighbor interpolation with rendering under various illuminations. 於 Proceedings of 2017 International Conference on Advances in Image Processing, ICAIP 2017 (頁 45-49). (ACM International Conference Proceeding Series; 卷 Part F131200). Association for Computing Machinery. https://doi.org/10.1145/3133264.3133269