Abstract | ||
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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 the color correction pipeline. We design and test new color correction pipelines that exploit different illuminant estimation and correction algorithms that are tuned and automatically selected on the basis of the image content. Since the illuminant estimation is an ill-posed problem, illuminant correction is not error-free. An adaptive color matrix transformation module is optimized, taking into account the behavior of the first module in order to alleviate the amplification of color errors. The proposed pipelines are tested on a publicly available dataset of RAW images. Experimental results show that exploiting the cross-talks between the modules of the pipeline can lead to a higher color-rendition accuracy. (c) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. |
Year | DOI | Venue |
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2013 | 10.1117/1.JEI.22.2.023014 | JOURNAL OF ELECTRONIC IMAGING |
Field | DocType | Volume |
Computer vision,Pipeline transport,Color space,Correction algorithm,Pattern recognition,Computer science,Matrix (mathematics),Color correction,Digital camera,Artificial intelligence,Standard illuminant,Transformation matrix | Journal | 22 |
Issue | ISSN | Citations |
2 | 1017-9909 | 6 |
PageRank | References | Authors |
0.52 | 20 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Simone Bianco | 1 | 226 | 24.48 |
Arcangelo Ranieri Bruna | 2 | 26 | 3.25 |
Filippo Naccari | 3 | 8 | 1.28 |
Raimondo Schettini | 4 | 1476 | 154.06 |