Hyperspectral images can identify minerals better than Multispectral images because of their high spectral resolutions. However, a pixel might include more than one mineral, as hyperspectral images have low spatial resolution. In these situations, the number of minerals can be estimated in mixed pixels but their spatial positions cannot be known. This is one of the biggest obstacles that prevents effective use of hyperspectral images in mineral exploration. In order to overcome that obstacle, it is known that, fusing hyperspectral images with a better spatial resolution images generates a better content in the fused images. In this study, well known and publicly available Cuprite AVIRIS image is fused with Landsat 8-Panchromatic band. Then, the minerals in the Cuprite site are classified both on the fused image and the original AVIRIS image. When we compared the classification results, it is found that, minerals are classified with higher accuracy on the fused image compared to the AVIRIS image.