The dichromatic color appearance of a chromatic stimulus T can be described if a stimulus S is found that verifies that a normal observer experiences the same sensation viewing S as a dichromat viewing T. If dichromatic and normal versions of the same color vision model are available, S can be computed by applying the inverse of the normal model to the descriptors of T obtained with the dichromatic model. We give analytical form to this algorithm, which we call the corresponding-pair procedure. The analytical form highlights the requisites that a color vision model must verify for this procedure to be used. To show the capabilities of the method, we apply the algorithm to different color vision models that verify such requisites. This algorithm avoids the need to introduce empirical information alien to the color model used, as was the case with previous methods. The relative simplicity of the procedure and its generality makes the prediction of dichromatic color appearance an additional test of the validity of color vision models.

An algorithm is proposed for the spectral and colorimetric characterization of digital still cameras (DSC) which allows them to be used as tele-colorimeters with CIE-XYZ color output, in cd/m 2 . The spectral characterization consists in the calculation of the color-matching functions from the previously measured spectral sensitivities. The colorimetric characterization consists in transforming the raw RGB digital data into absolute tristimulus values CIE-XYZ (in cd/m 2 ) under variable and unknown spectroradiometric conditions. Thus, in the first stage, a gray balance was applied over the raw RGB digital data to convert them into RGB relative colorimetric values. In the second stage, an algorithm of luminance adaptation versus lens aperture was inserted in the basic colorimetric profile. Capturing the ColorChecker chart under different light sources, and comparing the estimated XYZ data according to the developed color model in relation to the measured XYZ data (in cd/m 2 ) using a telespectroradiometer, we verified that the proposed characterization model may be broken down into two portions. Firstly, there is the basic colorimetric profile in combination with the new luminance adaptation algorithm. Secondly, there is the linear correction term due only to the mismatch of the color matching functions of the camera. Although the linear color correction term works relatively well, despite the imposed initial conditions (unknown spectral content of the scene), the separation of the proposed characterization model into two portions (raw and corrected performance) would allow the future comparison of various commercial cameras.

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We have compared corresponding pairs obtained by simultaneous matching (haploscopic matching) and by memory matching (after 10 minutes) using 34 reference tests selected from the Munsell Atlas (glossy) belonging to the four main hues 5Y, 5G, 5PB and 5RP. These colours lie very close to the F 1 and F 2 axis in the SVF space, where we have analysed our results. Illuminants D 65 and A were used as reference and matching illuminants, respectively. Our results show, for both kinds of matching, a tendency to select more colourful colours than the original ones, with significant differences between matching and test colours, whereas hue does not seem to follow a definite pattern. This behaviour is similar to that found in colour matching experiments without illuminant changes. The analogy does not hold for lightness, which in the present experiment does not seem to follow a clear pattern. The best matching colours lie along the red-green axis and the worst matching colours along the blue-yellow axis.