SUB-BLOCK PCA-WAVELET IMAGE SHARPENING APPROACH FOR HYPERSPECTRAL IMAGES

One of the most crucial issues to judge image quality is the spatial resolution. Hyperspectral image (HSI) sharpening is the process of combining spatial information to enhance spatial resolution of HSIs. Huge volumes of HSI data cause difficulties during the sharpening process. This paper proposed a practical and effective strategy to deal with HSI sharpening. We utilized sub-block method and combined PCA and wavelet fusion approaches to achieve the proposed scheme. Sub-block method helped reduce the calculation complexity and promote the efficiency. PCA and wavelet image sharpening contributed to enhance spatial resolution of HSI with less spectral distortion. The experiment demonstrated an efficient processing result and a good visualized effect. Qualitative and quantitative assessments were both used to evaluate the proposed approach.