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Due to the high flexibility of the spectral shape generated by a spectrally tunable multichannel LED light source, the traditional spectral estimation by a digital camera has difficulty in the training procedure and cannot reach a satisfactory accuracy. Considering the characteristics of the linear system for both lighting and imaging equipment, a method based on matrix factorization was proposed by capturing a standard color chart with its known reflectance illuminated under the individual channels of the multichannel LED light source. The experimental results indicate that the proposed method outperforms the traditional one, in terms of spectral accuracy and colorimetric difference, with the upper bound performance being higher than 0.999 goodness of fit coefficient (GFC) and less than 1.0 CIELAB unit, respectively.

High dynamic range (HDR) image acquisition techniques can record both bright and dark areas of the real scene. In order to acquire accurate colorimetric information as well as the luminance of the HDR scene, a reconstruction method in CIEXYZ device-independent color space based on camera colorimetric method was proposed in this paper. The camera RGB values of individual pictures are firstly transformed into the corresponding CIEXYZ values by colorimetric characterization with unrestricted capture settings. Then the XYZ values are fused by the weighting function determined according to the characterization accuracy. The prediction accuracy of the proposed method was verified by two phases of experiments to outperform the traditional one, with the color difference being less than 2 CIELAB units under the constant relative spectral power distribution (SPD) of lighting and 3.5 CIELAB units for the illuminations of different correlated color temperatures (CCTs), respectively.

Spectral estimation of fluorescent lamps is important in practical applications. Using an RGB digital camera and a standard color chart can be regarded as a multispectral way to recover lamp spectral characteristics that contain spikes or spectral lines. In this study, a new method for estimating the spectral power distribution (SPD) of fluorescent lamps was proposed with a workflow by applying two improvements to the existing reflectance recovery methods. The first improvement is to classify the estimated SPD into the corresponding type of fluorescent illuminant defined by CIE based on the spectral correlation distance, and the second one is to choose the optimized number of color patches for lamp SPD recovery with less error. The workflow consists of three modules, i.e. training, testing and optimization procedures. Compared with the traditional recovery method, the training procedure using synthetic data reduces the tremendous workload in practical measurements of different light sources. The testing results from synthetic and real data both indicate that these proposed modifications can significantly improve the accuracy of the existing recovery methods on colorimetric and spectral metrics. And by comparing their experimental results, three among five different methods are suggested to be suitable for the fluorescent lamp spectral estimation.

With colorimetric characterization, digital cameras can be used as image-based tristimulus colorimeters for color communication. In order to overcome the restriction of fixed capture settings adopted in the conventional colorimetric characterization procedures, a novel method was proposed considering capture settings. The method calculating colorimetric value of the measured image contains five main steps, including conversion from RGB values to equivalent ones of training settings through factors based on imaging system model so as to build the bridge between different settings, scaling factors involved in preparation steps for transformation mapping to avoid errors resulted from nonlinearity of polynomial mapping for different ranges of illumination levels. The experiment results indicate that the prediction error of the proposed method, which was measured by CIELAB color difference formula, reaches less than 2 CIELAB units under different illumination levels and different correlated color temperatures....