The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use o...

Means for optimally analyzing hyperspectral data has been a topic of study for some years. Our work has specifically focused on this topic since 19861. The point of departure for our study has been that of signal theory and the signal processing principles that have grown primarily from the communication sciences area over the last half century. The basic approach has been to seek a more fundam...

High-spectral resolution imaging provides critical insights into important computer vision tasks such as classification, tracking, and remote sensing. Modern Snapshot Spectral Imaging (SSI)systems directly acquire the entire 3D data-cube through the intelligent combination of spectral filters and detector elements. Partially because of the dramatic reduction in acquisition time, SSI systems exh...

Remote sensing may offer quick and economical methods of surveying road centerline geometry and condition. This research uses a combination of 4 m, 224-band AVIRIS hyperspectral imagery, and about 6000 field-gathered spectra, to develop a spectral library of urban materials. It attempts to extract roads of various types, and investigates the spectral signatures associated with different qualiti...

an ideal fusion method preserves the spectral information in fused image without spatial distortion. the pca is believed to be a well-known pan-sharpening approach and being widely used for its efficiency and high spatial resolution. however, it can distort the spectral characteristics of multispectral images. the current paper tries to present a new fusion method based on the same concept. in ...

During the last two decades, the number of spectral bands in optical remote sensing technology kept growing steadily going from multispectral (MS) to hyperspectral (HS) data sets. HS images employ hundreds of contiguous spectral bands to capture and process spectral information over a range of wavelenghts, compared to the tens of discrete spectral bands used in MS images (Chang, 2003). This inc...

Hyperspectral images contain rich and fine spectral information, an improvement of land use/cover classification accuracy is expected from the use of such images. However, the classification methods that have been successfully applied to multispectral data in the past are not as effective as to hyperspectral data. The major cause is that the size of training data set does not correspond to the ...

This paper presents a novel technique, namely texture-guided multisensor superresolution (TGMS), for fusing a pair of multisensor multiresolution images to enhance the spatial resolution of a lower-resolution data source. TGMS is based on multiresolution analysis, taking object structures and image textures in the higher-resolution image into consideration. TGMS is designed to be robust against...