Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Estimating the spectral sensitivity of a digital sensor using calibration targets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Color measurements with a consumer digital camera using spectral estimation techniques
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Color device calibration: a mathematical formulation
IEEE Transactions on Image Processing
Spectralization: reconstructing spectra from sparse data
EGSR'10 Proceedings of the 21st Eurographics conference on Rendering
Colour matching function learning
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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Simple and effective geometric and radiometric calibration of camera devices has enabled the use of consumer digital cameras for HDR photography, for image based measurement and similar applications requiring a deeper understanding about the camera characteristics. However, to date no such practical methods for estimating the spectral response of cameras are available. Existing approaches require costly hardware and controlled acquisition conditions limiting their applicability. Consequently, even though being highly desirable for color correction and color processing purposes as well as for designing image-based measurement or photographic setups, the spectral response of a camera is rarely considered. Our objective is to close this gap. In this work a practical approach for multi-spectral characterization of trichromatic cameras is presented. Taking photographs of a color chart and measuring the average lighting using a spectrophotometer the effective spectral response of a camera can be estimated for a wide range of out-of-lab environments. By comprehensive cross validation experiments we prove that the new method performs well compared to costly reference measurements. Moreover, we show that our technique can also be used to generate ICC profiles with higher accuracy and less constrained capturing conditions compared to state-of-the-art ICC profilers.