Reflectance reconstruction for multispectral imaging by adaptive Wiener estimation

Hui Liang Snen, Pu Qing Cai, Si Jie Shao, John Haozhong Xin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

104 Citations (Scopus)


In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The performance of the proposed adaptive Wiener estimation and the traditional method are compared in the cases of different channel numbers and noise levels. Experimental results show that the proposed method outperforms the traditional method in terms of both spectral and colorimetric prediction errors when the imaging channel number is 7 or less. When the imaging system consists of 11 or more channels, the color accuracy of the proposed method is slightly better than or becomes close to that of the traditional method.
Original languageEnglish
Pages (from-to)15545-15554
Number of pages10
JournalOptics Express
Issue number23
Publication statusPublished - 12 Nov 2007

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics


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