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The intention for fusion of low-spatial-resolution hyperspectral image (HSI) and high-spatial-resolution multi-spectral image (MSI) is to obtain a high-resolution image in both spectral and spatial domains, which is more suitable for object identification and precise positioning. A novel fusion algorithm for HSI and MSI is proposed in this paper to obtain a better spectral preserving performance....
Spatial resolution is one of the most expensive and hardest to improve in imaging systems. An efficient spatial-spectral data fusion method for superresolution of hyperspectral (HS) imagery through exploiting the spatial correlation of the endmembers using a superresolution mapping (SRM) technique is proposed in this paper. Endmember abundances (fractional images) obtained using linear mixture model...
Hyperspectral technology has introduced a new perspective in remote sensing applications but suffers from low spatial resolution. A new spatial-spectral data fusion technique based on spectral mixture analysis and super-resolution mapping for spatial resolution enhancement of hyperspectral imagery is proposed in this paper. To this end a linear mixture model and a fully constrained least squares based...
The 25 km resolution standard wind products (L2B) are available operationally in near-real time from SeaWinds on QuikSCAT. This relatively low resolution can be enhanced to yield a 2.5 km ultra-high resolution (UHR) product that can be used to identify hurricane eye centers more accurately. A comparison is made between the analyst's choice of eye location based on UHR images and interpolated best-track...
Although techniques for resolution enhancement in single-aspect radar imaging have made rapid progress in recent years, it does not necessarily imply that such enhanced images will improve target identification or recognition. However, when multiple looks of the same target from different aspects are obtained, the available knowledge increases, allowing more useful target information to be extracted...
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