Calibrating spectral images using penalized likelihood

G.W.A.M. van der Heijden, C. Glasbey

    Research output: Contribution to journalArticleAcademicpeer-review

    9 Citations (Scopus)

    Abstract

    A new method is presented for automatic correction of distortions and for spectral calibration (which band corresponds to which wavelength) of spectral images recorded by means of a spectrograph. The method consists of recording a bar-like pattern with an illumination source with spectral bands (e.g. neon or mercury). Using prior information of the wavelength of these spectral bands and the spatial arrangement of the bars, a template image is constructed where the spectral axis is linearly related with wavelength. Next, a grid is posed on both the recorded and template image. Using a penalized likelihood method in a quasi-Newton iterative optimization technique, points of the grid on the recorded image are shifted such that the transformed (warped) image has a high resemblance (likelihood) to the template image and a low distortion (penalty term). The method is fully automatic and does not require any landmark extraction. After the transformation grid has been established, every new recorded image can be corrected in real time for any spectral and spatial distortion using fast bilinear interpolation. Recalibration of the system can be done reasonably fast using a previously calculated grid
    Original languageEnglish
    Pages (from-to)231-236
    JournalReal-Time Imaging
    Volume9
    Issue number4
    DOIs
    Publication statusPublished - 2003

    Keywords

    • algorithm

    Fingerprint Dive into the research topics of 'Calibrating spectral images using penalized likelihood'. Together they form a unique fingerprint.

    Cite this