Alessandro Barducci

Theoretical and experimental assessment of noise effects on least-squares spectral unmixing of hyperspectral images

The problem of input noise affecting the subpixel classifica- tion is examined in order to assess its relationship with the output noise. The approach followed in this study was to investigate the output noise level obtained with a least-squares subpixel classification algorithm ap- plied to simulated spectra. The simulation of mixed pixel spectra took into account variable pixel composition and a selectable power of the superimposed noise. Noise was considered a zero-mean stochastic pro- cess over wavelength that was assumed to be jointly normal and uncor- related. The paper outlines the structure and the mathematical proper- ties of the performed unmixing simulations, and clearly shows the relationship between input and output noise. It is shown that a simple exponential law relates with substantial accuracy the standard deviation of input noise to that of the computed subpixel abundances for fully constrained unmixing. As expected, the cases of unconstrained and abundances sum to one partially constrained unmixing are controlled by a linear relationship between input and output noise amplitude. The paper also shows the dependence of unmixed abundances and output noise on the spectral similarity of end members involved in the unmixing. Three subpixel classification approaches unconstrained, partially con- strained, and fully constrained algorithms were investigated.

Theoretical aspects of Fourier Transform Spectrometry and common path triangular interferometers

Recent investigations have induced relevant advancements of imaging interferometry, which is becoming a viable option for Earth remote sensing. Various research programs have chosen the Sagnac configuration for new imaging interferometers. Due to the growing diffusion of this technique, we have developed a self-contained theory for describing the signal produced by triangular FTSs and its optimal processing. We investigate the relevant disadvantages of multiplexing, and compare dispersive with FTS instruments. The paper addresses some methods for correcting the phase error, and the non-unitary transformation performed by a Sagnac interferometer. The effect of noise on spectral estimations is discussed.

Multispectral fusion of multisensor image data by the generalized Laplacian pyramid

Presents a general and formal solution to the problem of multisensor image data fusion and applies its results to a specific case study concerning multi-spectral observations: Landsat TM (30 m resolution) and MOMS-2P (18 m). The proposed scheme relies on the generalized Laplacian pyramid, which is a non-dyadic band-pass analysis structure unconstrained from the ground scales of the imaged data: for a p/q>1 ratio only one low-pass filter with cut-off at 1/p of the spatial frequency content is needed. Filter design is easy and noncritical for performances. Thus, the pyramid method is simple to be designed and generalized to images having whatsoever ground resolution, as in most applications involving new-generation sensors.

Analysis and rejection of systematic disturbances in hyperspectral remotely sensed images of the Earth

We discuss the appearance of systematic spatial and spectral patterns of noise in remotely sensed images as well as the possibility of mitigating the effects of these patterns on the data. We describe the structure of two simple theoretical models that predict the appearance of patterns of noise (mainly stripe noise). Moreover, two new algorithms that have been specifically developed to mitigate the noise patterns are described. The performance of the two algorithms is assessed by use of some hyperspectral images acquired by different kinds of airborne sensor. The algorithms show an unexpected ability to reject these noise patterns.

Infrared detection of active fires and burnt areas: theory and observations

We have investigated the problem of fire recognition and management using hyperspectral images remotely sensed by the multispectral infrared and visible imaging spectrometer (MIVIS). Twenty near infrared bands (between 1.99 and 2.48 μm) and ten thermal infrared (between 8.2 and 12.7 μm) MIVIS bands have been utilised. The main problems addressed in this work are the fire-front and burned-area recognition and the extraction of information useful for the management of the burned area. The paper shows data gathered by the sensor MIVIS over the fire, the data processing result and is completed with a brief theoretical discussion of the involved topics. Some hints are given about the diagnostic capabilities of other hyperspectral devices.

Effects of light pollution revealed during a nocturnal aerial survey by two hyperspectral imagers

A remote-sensing campaign was performed in September 2001 at nighttime under clear-sky conditions before moonrise to assess the level of light pollution of urban and industrial origin. Two hyperspectral sensors, namely, the Multispectral Infrared and Visible Imaging Spectrometer and the Visible Infrared Scanner-200, which provide spectral coverage from the visible to the thermal infrared, were flown over the Tuscany coast (Italy) on board a Casa 212 airplane. The acquired images were processed to produce radiometrically calibrated data, which were then analyzed and compared with ground-based spectral measurements. Calibrated data acquired at high spectral resolution (approximately 2.5 nm) showed a maximum scene brightness almost of the same order of magnitude as that observed during similar daytime measurements, whereas their average luminosity was 3 orders of magnitude lower. The measurement analysis confirmed that artificial illumination hinders astronomical observations and produces noticeable effects even at great distances from the sources of the illumination.

Aerospace wetland monitoring by hyperspectral imaging sensors: A case study in the coastal zone of San Rossore Natural Park

The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces.

Estimation of Normalized Atmospheric Point Spread Function and Restoration of Remotely Sensed Images

The Earths atmosphere heavily affects the remote sensing images collected by spaceborne passive optical sensors due to radiation-matter interaction phenomena like radiation absorption, scattering, and thermal emission. A complex phenomenon is the adjacency effect, i.e., radiation reflected by the ground that, due to the atmospheric scattering, is being seen in a viewing direction different from that corresponding to the ground location that reflected it. Adjacency gives rise to crosstalk between neighboring picture elements up to a distance that depends on the width of the integral kernel function employed for the mathematical modeling of the problem. As long as the atmosphere is a linear space-invariant system, the adjacency can be modeled as a low-pass filter, with the atmospheric point spread function (APSF) applied to the initial image. In this paper, a direct method of estimating the discrete normalized APSF (NAPSF) using images gathered by high-resolution optical sensors is discussed. We discuss the use of the NAPSF estimate for deducing the Correction Spatial high-pass Filter (CSF)-a correction filter that removes the adjacency effect. The NAPSF estimation procedure has been investigated using statistical simulations, whose outcomes permitted us to identify the conditions under which the NAPSF could be measured with acceptable errors. The NAPSF estimation is examined for various natural images acquired by MOMS-2P, CHRIS, AVIRIS, and MIVIS.

Abnormal oral mucosal light reflectance: a new clinical marker of high risk for colorectal cancer

Background: A familial predisposition to colorectal cancer (CRC) has been clearly established, consisting of familial clustering in 15–20% and clear hereditary aetiology in 5–10% of overall CRC cases. Early identification of families and individuals at high risk is essential as intensive surveillance has been demonstrated to reduce cancer incidence and overall mortality. In the present study, the value of oral mucosal light reflectance in identifying hereditary non-polyposis colorectal cancer (HNPCC) carriers was investigated. Methods: Twenty members of six different genetically unrelated HNPCC kindred and 30 genetically unrelated age and sex matched healthy controls were examined. Lower gingival and vestibular oral mucosal reflectance was measured using an imaging spectrophotometer. Results: HNPCC carriers showed significantly lower values in the 590–700 nm wavelength range (p⩽0.0004). A reflectance cut off value ⩽47.9% at the 700 nm wavelength discriminated between HNPCC carriers and controls, with 100% sensitivity and 100% specificity. Conclusions: These findings may provide an additional phenotypic sign in HNPCC carriers, which could be used in first level CRC population screening programmes.

Solar spectral irradiometer for validation of remotely sensed hyperspectral data

A new solar spectral irradiometer that operates in the visible and near-infrared spectral ranges has been developed. This instrument takes advantage of a new concept optical head that collects the light that impinges on a hemispheric surface, thus improving the instrument angular response with respect to traditional devices. The technical characteristics of the instrument are investigated and detailed, and its radiometric calibration, performed by means of a Langley-like method, is discussed. A new simplified theoretical model that accounts for the diffuse irradiance observed in an optically thin plane-parallel atmosphere has been developed to improve the fit of the irradiance diurnal evolution. An alternative polynomial parametric representation of monochromatic diffuse irradiance evolution has been attempted, but satisfactory results were not obtained from the fitting of experimental data. The new instrument could be useful to carry out remote-sensing validation campaigns.