Vibrational spectroscopic imaging (infrared and Raman) is a powerful technique for visualizing the distribution of chemical compounds of complex samples. Due to the very high content of information contained in their spectrum, vibrational spectroscopies have taken more and more importance in molecular imaging. With such far-field imaging spectroscopy, the resolution limit is first and foremost dictated by the photon wavelength due to diffraction limit. This becomes a real constraint when micron-sized or submicron-sized samples are analyzed because no more details are present in generated images. Thus increasing the spatial resolution is still a major challenge for a better characterization of the analyzed samples. Two approaches have emerged to go beyond this limit. The first approach focuses on the instrumental development such as the near-field spectroscopy. The second approach is an algorithmic one. It attempts to push the limits of resolution of optical system by the mathematical analysis of images generated on conventional far-field spectrometers. The aim of the presented work is to develop and optimize of a new concept called "super-resolution" in imaging for mid-infrared, near infrared and Raman spectroscopy in order to increase the spatial resolution. Different samples forms of pharmaceutical, biological or environmental origins will be exploited.
