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Muon Scattering Tomography (MST) has been shown to be a powerful techniquefor the non-invasive imaging of high-shielded objects. We present here theapplication of the MST technique to investigate two types of nuclear wastepackages, a small-steel drum and a large nuclear waste cask, namely, a CASTORV/52. We have developed a quantitative method using the contrast-to-noise ratio(CNR) to evaluate the performance of an MST detector system in differentiatingbetween high-, medium-, and low-Z materials inside nuclear waste packages withdifferent shielding types. This study reveals that our MST detector system isable to differentiate between a (10 $\times$ 10 $\times$ 10 cm$^3$) uraniumcube, embedded within a concrete matrix inside the small-steel drum, andregions of background signal in six hours of muon exposure time with a CNRvalue of 3.1$\pm$0.2. During our investigation of the highly-shielded cask, thereconstructed images of the cask contents indicated the ability of our systemto detect irregular baskets, such as empty baskets, with a CNR value of5.0$\pm$0.3 after 30 days of muon exposure. These studies were done using aMonte Carlo simulation tuned to the performance of resistive plate chambers(RPCs) based muon tomography system built by the University of Bristol, whichhad a reported position resolution of 350 micron.  Here we also report the dependence of the performance on the positionresolution. We argue that using a combination of RPC and drift chambers (DC)detectors with 700 micron and 4 mm position resolutions respectively is able togenerate tomographic images of well-shielded materials in a few hours of muonexposure time. With these position resolutions, our system needs six hours ofmuon exposure time to produce a good quality image of a cube of uranium withside-length of 10 cm shielded by a concrete matrix with CNR value of2.4$\pm$0.25.

A quantitative assessment of Imaging High-Z and Medium-Z materials using Muon Scattering Tomography