Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Multispectral remote sensing applications from UAS are reported in the literature less commonly than applications using visible bands, although light-weight multispectral sensors for UAS are being us...

Although it is well recognized that photointerpretation of the Landsat imagery can provide adequate information for mapping broad categories of land cover at a reconnaissance level, it is also true that the Landsat data in digital format (CCT's) together with numerical (computer-aided) analysis techniques can provide a great deal more information at a higher level of mapping detail with mapping...

Automated segmentation of tumors from a multispectral data set like that of the Magnetic Resonance Images (MRI) is challenging. Independent Component Analysis (ICA) and its variations for Blind Source Separation (BSS) have been employed in previous studies but have met with cumbersome obstacles due to its inherent limitations. Here we have approached the multispectral data set initially with fe...

A pixel level data fusion approach based on correspondence analysis (CA) is introduced for high spatial and spectral resolution satellite data. Principal component analysis (PCA) is a well-known multivariate data analysis and fusion technique in the remote sensing community. Related to PCA but a more recent multivariate technique, correspondence analysis, is applied to fuse panchromatic data wi...

OBJECTIVE This review evaluates the diagnostic efficacy of fluorescence spectroscopy, reflectance spectroscopy, and their combination that use both point probe and multispectral imaging approaches in diagnosing cervical neoplasia in vivo. METHODS Articles were selected for this review from a literature search which report the performance of fluorescence and reflectance spectroscopy devices in...

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...

a r t i c l e i n f o Remote sensing can be considered a key instrument for studies related to forests and their dynamics. At present, the increasing availability of multisensor acquisitions over the same areas, offers the possibility to combine data from different sensors (e.g., optical, RADAR, LiDAR). This paper presents an analysis on the fusion of airborne LiDAR and satellite multispectral ...