The assignment of a quantitative spectral image quality metric is discussed with an approach proposed. Quality is divided into fidelity and utility components, with utility studied in the context of object detection in hyperspectral imagery. ©2010 Optical Society of America OCIS codes: (110.3000) Image quality assessment; (110.4234) Multispectral and hyperspectral imaging; (280.4788) Optical se...

To enable industrial adoption of hyperspectral imaging we have developed a unique integrated hyperspectral filter/imager technology. The spectral filters are monolithically deposited/integrated on top of CMOS imagers at wafer level. The materials of the filters are chosen such that they are compatible with the production flows available in most CMOS foundries. The result is a compact & fast hyp...

Hyperspectral remote sensing is used in precision agriculture to remotely and quickly acquire crop phenotype information. This paper describes the generation of a digital orthophoto map (DOM) and radiometric calibration for images taken by a miniaturized snapshot hyperspectral camera mounted on a lightweight unmanned aerial vehicle (UAV). The snapshot camera is a relatively new type of hyperspe...

River floodplains in the Netherlands serve as water storage areas, while they also have the function of nature rehabilitation areas. Floodplain vegetation is therefore subject to natural processes of vegetation succession. At the same time, vegetation encroachment obstructs the water flow into the floodplains and increases the flood risk for the hinterland. Spaceborne pointable imaging spectros...

I n recent years, it has become clear that hyperspectral imaging has formed a core area within the geoscience and remote sensing community. Armed wi th advanced optical sensing technology, hyperspectral imaging offers high spectral resolution—a hyperspectral image can contain more than 200 spectral channels (rather than a few channels as in multispectral images), covering visible and near-infra...

Integrating spectral and spatial information is proved effective in improving the accuracy of hyperspectral imagery classification. In recent studies, two kinds of approaches are widely investigated: (1) developing a multiple feature fusion (MFF) strategy; and (2) designing a powerful spectral-spatial feature extraction (FE) algorithm. In this paper, we combine the advantages of MFF and FE, and...

The requirements of reliability, expeditiousness, accuracy, consistency, and simplicity for quality assessment of food products encouraged the development of non-destructive technologies to meet the demands of consumers to obtain superior food qualities. Hyperspectral imaging is one of the most promising techniques currently investigated for quality evaluation purposes in numerous sorts of appl...

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be ex...

1.0 Introduction Imaging Spectrometry data or Hyperspectral Imagery (HSI) acquired using airborne systems have been used in the geologic community since the early 1980’s and represent a mature technology (Goetz et al., 1985; Kruse et al., 1999). The solar spectral range, 0.4 to 2.5 μm, provides abundant information about many important Earth-surface minerals (Clark et al., 1990). In particular,...