6533b82dfe1ef96bd1291c03
RESEARCH PRODUCT
Representation and estimation of spectral reflectances using projection on PCA and wavelet bases
Tadeusz SliwaYvon VoisinJon Yngve HardebergAlamin Mansourisubject
Mathematical optimizationbusiness.industryGeneral Chemical EngineeringMultispectral imageHuman Factors and ErgonomicsBasis functionPattern recognitionGeneral ChemistryInverse problemsymbols.namesakeWaveletFourier transformRobustness (computer science)Principal component analysissymbolsFunction representationArtificial intelligencebusinessMathematicsdescription
In this article, we deal with the problem of spectral reflectance function representation and estimation in the context of multispectral imaging. Because the reconstruction of such functions is an inverse problem, slight variations in input data completely skew the expected results. Therefore, stabilizing the reconstruction process is necessary. To do this, we propose to use wavelets as basis functions, and we compare those with Fourier and PCA bases. We present the idea and compare these three methods, which belong to the class of linear models. The PCA method is training-set dependent and confirms its robustness when applied to reflectance estimation of the training sets. Fourier and wavelet bases allow good generalization; an advantage of wavelets is that they avoid boundary artifacts. The results are evaluated with the commonly used goodness-of-fit coefficient (GFC), and the reliability of the use of wavelets is proved. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 485–493, 2008
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2008-12-01 | Color Research & Application |