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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. © 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.

The color reproduction accuracy is a key factor to the overall perceived image quality in digital photography. In this framework, both the illuminant estimation process and the color correction matrix concur in the formation of the overall perceived image quality. To the best of our knowledge, the two processes have always been studied separately, thus ignoring the interactions between them. We investigate here these interactions, showing how the color correction transform amplifies the illuminant estimation errors. We demonstrate that incorporating knowledge about the illuminant estimation behavior in the optimization of the color correction matrix makes it possible to alleviate the error amplification. Different strategies to improve color accuracy under both perfect and imperfect white point estimations are investigated, and the experimental results obtained with a digital camera simulator are reported. © 2012 Optical Society of America.

In this paper we present a preliminary study towards the design of a low cost colorimetric imaging device. We show that an effective color measurement is possible even using consumer camera sensors. We present here the colorimetric accuracy test results obtained with simulated data using the theoretical model of image formation and a camera simulation system. The final paper will also include the colorimetric accuracy test results obtained with real camera sensors. For all the experiments the multispectral response has been obtained by the overlap of colored filters on the existing color filter array pattern. Many consumer devices can benefit from the colorimetric accuracy of such a system, e.g. printers with automatic color management characterization or other consumer devices where an accurate color response is required. © 2011 IEEE.

The illuminant estimation has an important role in many domain applications such as digital still cameras and mobile phones, where the final image quality could be heavily affected by a poor compensation of the ambient illumination effects. In this paper we present an algorithm, not dependent on the acquiring device, for illuminant estimation and compensation directly in the color filter array (CFA) domain of digital still cameras. The proposed algorithm takes into account both chromaticity and intensity information of the image data, and performs the illuminant compensation by a diagonal transform. It works by combining a spatial segmentation process with empirical designed weighting functions aimed to select the scene objects containing more information for the light chromaticity estimation. This algorithm has been designed exploiting an experimental framework developed by the authors and it has been evaluated on a database of real scene images acquired in different, carefully controlled, illuminant conditions. The results show that a combined multi domain pixel analysis leads to an improvement of the performance when compared to single domain pixel analysis.