CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) hyperspectral data have a spatial resolution ranging from 12 to 36m/pixel allowing the high resolution mapping of minerals at the surface of Mars. However, the signal-to-noise ratio (SNR) makes challenging the discrimination of minerals spectrally close such as certain phyllosilicates and carbonates. Here, we discuss different processing of data reduction used to improve the signal-to-noise ratio and to highlight the alteration minerals at the surface of Mars and their limit. We show that our tool allows to understand trends in global mineralogy present in hyperspectral data cube.