Pigments characterization on paintings is usually made with X-ray fluorescence, traditional false color photography and optical microscopy. The use of optical techniques based on reflectance spectra, like reflectance spectrophotometry or hyperspectral imaging, is limited today to some case studies. We would like to improve these optical techniques for pigment characterization, because they are non-invasive and can give a lot of information. After comparing the ways to calibrate to reflectance spectrophotometry and hyperspectral imaging, we develop the two techniques for the specific study of pigments. We develop a Matlab program to analyze (identify and quantify) reflectance spectra given by spectrophotometry, and a new methodology based on false color composites to use hyperspectral images in a simple way. The choice of the spectral bands to identify pigments takes its roots in the maximization of spectral differences, and leads to the generation of 3 false color composites - called variable composites FC1, FC2 and FC3 - to distinguish the pigments of the four categories (blue, red, yellow and green). The results of spectrophotometry and variable composites on a painting of the 17^th century by French painter Eustache Le Sueur are encouraging and consistent with other techniques' results. Our results should promote the use of spectrophotometry and hyperspectral imaging for pigment characterization in the future.