|
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acquired from
a given scene (or specific object) at a short, medium or long distance by an airbone or satellite sensor. Over the
last few years, hyperspectral image data sets have been collected for a great amount of locations over the world,
using a variety of instruments for Earth observation. Despite the increasing importance of hyperspectral images
in remote sensing applications, there is no common repository of hyperspectral data intended to distribute and
share hyperspectral data sets in the community. Quite opposite, the hyperspectral data sets which are available
for public use are spread among different storage locations and present significant heterogeneity regarding the
storage format, associated meta-data (if any), or ground-truth availability. As a result, the development of
a standardized hyperspectral data repository is a highly desired goal in the remote sensing community. In
this paper, we take a necessary first step towards the development of a digital repository for remotely sensed
hyperspectral data. The proposed system allows uploading new hyperspectral data sets along with meta-data,
ground-truth and analysis results, with the ultimate goal of sharing publicly available hyperspectral images within
the remote sensing community. The database has been designed in order to allow storing relevant information for
the hyperspectral data available through the system, including basic image characteristics (width, height, number
of bands, format) and more advanced meta-data (ground-truth information, publications in which the data has
been used). The current implementation consists of a front-end to ease the management of images through
a web interface, thus containing both synthetic and real hyperspectral images from two highly representative
instruments, such as NASAs Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite Mining
District in Nevada. Most importantly, the developed system includes a spectral unmixing-based content based
image retrieval (CBIR) functionality which allows searching for images on the spectral unmixing information
(spectrally pure components or endmembers and their associated abundances in the scene). This information
is stored as meta-data associated to each hyperspectral image instance, and then used to search and retrieve
images based on information content. This paper presents the design of the system and a preliminary validation
of the unmixing-based retrieval functionality using both synthetic and real hyperspectral images stored in the
database.
|
