Owing to a large number of spectral bands, it is always a challenge to devise an optimal visualization method for hyperspectral images. An algorithm must maintain a balance between dimensionality reduction and restoration of maximum spectral information. A methodology for visualization of hyperspectral imagery is proposed based on extraction of salient regions. For that, spectral bands are selected from different combinations of principal component analysis, minimum noise fraction, and saliency maps. A hierarchical fusion method is proposed, which is applied on the selected bands to obtain a final three band RGB image. The qualitative and quantitative results of the proposed method are very encouraging once compared with other state-of-the-art methods.