2013
DOI: 10.1117/1.jei.22.2.023014
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Color correction pipeline optimization for digital cameras

Abstract: Abstract. The processing pipeline of a digital camera converts the RAW image acquired by the sensor to a representation of the original scene that should be as faithful as possible. There are mainly two modules responsible for the color-rendering accuracy of a digital camera: the former is the illuminant estimation and correction module, and the latter is the color matrix transformation aimed to adapt the color response of the sensor to a standard color space. These two modules together form what may be called… Show more

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Cited by 38 publications
(19 citation statements)
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“…As future work we plan to extend the spectral reconstruction to uncontrolled light setups, where a light estimation and correction step is needed to render the scene as taken under a canonical light (Bianco, Bruna et al, 2012, Bianco, Bruna et al, 2013, Bianco & Schettini, 2014. We will also investigate the use of more complex metrics to compare the acquisition taken with different devices: instead of using single-valued metrics, we will investigate the use of metrics able to output an error map combining both colorimetric and structural errors (Bianco, Ciocca et al, 2009).…”
Section: Resultsmentioning
confidence: 99%
“…As future work we plan to extend the spectral reconstruction to uncontrolled light setups, where a light estimation and correction step is needed to render the scene as taken under a canonical light (Bianco, Bruna et al, 2012, Bianco, Bruna et al, 2013, Bianco & Schettini, 2014. We will also investigate the use of more complex metrics to compare the acquisition taken with different devices: instead of using single-valued metrics, we will investigate the use of metrics able to output an error map combining both colorimetric and structural errors (Bianco, Ciocca et al, 2009).…”
Section: Resultsmentioning
confidence: 99%
“…Industrial applications include the use as an analysis tool to compare the raw performance of commercial cameras [MPVC03]; in colorimetry, to perform colour characterization of displays and projectors, and, in general, the absolute measurement of non‐homogeneous samples, given the possibility of simultaneously measuring the whole visual field. As future work, we plan to investigate the applicability of the proposed technique to more complex processing pipelines [BBNS12, BBNS13].…”
Section: Discussionmentioning
confidence: 99%
“…Finally, the interpolated raw image is converted in a color image using a color conversion matrix (CCM) which maps the intrinsic input spectral space given by the camera to an output color space. We choose CIE-XYZ 1931 [8]- [10] as reference for output space because one can then easily convert XYZ coordinates in any display space such as sRGB. The image formation flow is schemed Figure 2.…”
Section: Model Of Signal Acquisition and Color Image Formationmentioning
confidence: 99%