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Spectral calibration of digital cameras based on the spectral data of commercially available calibration charts is an ill-conditioned problem that has an infinite number of solutions. We introduce a method to estimate the sensor's spectral sensitivity function based on metamers. For a given patch on the calibration chart we construct numerical metamers by(More)
A standard approach to generating a greyscale equivalent to an input colour image involves calculating the so-called structure tensor at each image pixel. Defining contrast as associated with the maximum-change direction of this matrix, the grey gradient is identified with the first eigenvector direction, with gradient strength given by the square root of(More)
The set of metamers for a given device response can be calculated given the device's spectral sensitivities. Knowledge of the metamer set has been useful in practical applications such as color correction and reflectance recovery. Unfortunately, the device sensitivities of a camera or scanner are not known, and they are difficult to estimate reliably(More)
The gamut of a colour space is defined by a number of extreme points. The best inks to achieve an accurate spectral reproduction of a given target are those which span the tar-get's spectral gamut. Using a modified non-negative matrix factorization (NMF) algorithm we derive m colorants and their spectral curves such that they are the extreme points of the(More)
A standard approach to generating a grayscale equivalent to an input multi-spectral image involves calculating the so-called structure tensor at each image pixel. Defining contrast as associated with the maximum-change direction of this matrix, the gray gradient is identified with the first eigenvector direction, with gradient strength given by the square(More)