Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization

An Improved Super-Resolution with Manifold Learning and Histogram Matching

Biometric Person Authentication such as face, fingerprint, palmprint and signature depends on the quality of image processing. When it needs to be done under a low-resolution image, the accuracy will be impaired. So how to recover the lost information from downsampled images is important for both authentication and preprocessing. Based on Super-Resolution through Neighbor Embedding algorithm an...

Super-resolution land-cover mapping based on the selective endmember spectral mixture model in hyperspectral imagery

An Efficient Technique for Hyperspectral Endmember Extraction based on SE

Hyperspectral Endmember extraction of a set of accurateendmembers is critical for the proper unmixing of Hyperspectral image. Several preprocessing algorithms such as spatial preprocessing (SPP), region based spatial preprocessing (RBSPP), and spatial spectral preprocessing (SSPP) have been developed for the extraction of endmembers. These algorithms require complex operations and huge computat...

Super-resolution of Hyperspectral Images Using Compressive Sensing Based Approach

Over the past decade hyper spectral (HS) image analysis has turned into one of the most powerful and growing technologies in the field of remote sensing. While HS images cover large area at fine spectral resolution, their spatial resolutions are often too coarse for the use in various applications. Hence improving their resolution has a high payoff. This paper presents a novel approach for supe...

Hyperspectral Super-Resolution with Spectral Unmixing Constraints

Hyperspectral sensors capture a portion of the visible and near-infrared spectrum with many narrow spectral bands. This makes it possible to better discriminate objects based on their reflectance spectra and to derive more detailed object properties. For technical reasons, the high spectral resolution comes at the cost of lower spatial resolution. To mitigate that problem, one may combine such ...