In this work, mid-infrared hyperspectral images of multilayer polymer film (MLPF) cross sections are acquired with a high-speed quantum cascade laser (QCL) based mid-infrared microscope and analyzed using different data analysis techniques. The investigated MLPF is a polypropylene (PP) and ethylene-vinyl alcohol co-polymer (EVOH) composite commonly used for food packaging due to its outstanding barrier characteristics. Pure band integration of supposedly selective absorption bands for the two constituents of the MLPF is compared to principal component analysis (PCA) and multivariate curve resolution (MCR) algorithms regarding the ability to spatially resolve the differently composed areas in the MLPF. While both pure band integration and PCA are strongly affected by common physical artifacts in the spectral data, such as sample tilt, scattering or interference effects, MCR managed to give a clear picture of the composition of the MLPF, which matches the actual situation given by the manufacturing process. The obtained results can guide the way to the application of highperformance mid-infrared spectroscopic instrumentation for spatially resolved polymer analysis by meaningful interpretation of hyperspectral image data.