6533b82efe1ef96bd1293a6f

RESEARCH PRODUCT

Optical calibration of a multispectral imaging system based on interference filters

Franck MarzaniJon Yngve HardebergPierre GoutonAlamin Mansouri

subject

DeblurringComputer sciencebusiness.industryNoise reductionWiener filterMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage processingReal imageAtomic and Molecular Physics and OpticsMultispectral pattern recognitionsymbols.namesakeComputer Science::GraphicsInterference (communication)Computer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceOptical filterFocus (optics)businessImage restoration

description

We present a new approach to optically calibrate a multispectral imaging system based on interference filters. Such a system typically suffers from some blurring of its channel images. Because the effectiveness of spectrum reconstruction depends heavily on the quality of the acquired channel images, and because this blurring negatively affects them, a method for deblurring and denoising them is required. The blur is modeled as a uniform intensity distribution within a circular disk. It allows us to characterize, quantitatively, the degradation for each channel image. In terms of global reduction of the blur, it consists of the choice of the best channel for the focus adjustment according to minimal corrections applied to the other channels. Then, for a given acquisition, the restoration can be performed with the computed parameters using adapted Wiener filtering. This process of optical calibration is evaluated on real images and shows large improvements, especially when the scene is detailed.

https://doi.org/10.1117/1.1839889