Proc. SPIE. 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII
KEYWORDS: Mathematical modeling, Signal to noise ratio, Short wave infrared radiation, Sensors, Calibration, Satellites, Remote sensing, Image resolution, Interference (communication), Clouds, Image registration, Satellite imaging, Systems modeling, Simulation of CCA and DLA aggregates, Algorithms
WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.
Atmospheric spectra reconstructed from interferometric measurements are susceptible to scene motion, which can be caused by changing environment or instrument jitter. This leads to a coupling between the time series of the modulated scene radiance and the interferogram collected as a function of time. Spectral artifacts are generated when this occurs and appear as both narrow, isolated spikes in the measurement wavelength band as well as broad, out-of-band features. Here, we derive an analytical relationship that depends on jitter frequency, amplitude and phase, and the scene gradient. The observed radiance is expressed as a spatially weighted mixture of radiance originating from various points within the scene. Spectral artifacts created by relative scene motion are shown to be proportional to the radiometric scene difference within the instrument field of view (FOV) and jitter amplitude, and vary significantly with the jitter frequency. The analytical solution can be useful in various applications, where image instability is expected to have an effect on measurements in question, ranging from spectroscopy of turbine plumes, through airborne measurements of smoke density and chemical composition in natural fire or volcanic events, to atmospheric sounding from space.
The capability of the WorldView-2 (WV02) satellite is analyzed for bathymetric applications in shallow coastal
waters. We use an Optimal Estimation method, which provides lower bounds on retrievals errors for an idealized
sensor and idealized model of the environment. Retrieval performance is studied over different substrates and
column water properties. We also study effects of increased signal to noise ratio. This analysis is supported by
numerical inversion of imagery, using a variant of a least-square optimization. Results from 4 different study areas
collected across a few sites in clear Case 1 and Case 2 waters show that the water depth can be realistically
measured on a pixel-by-pixel basis with 10% standard deviation of the error, down to nearly 20 meters depth in Case
1 waters over bright sandy bottom. The same accuracy over dark sea grass or coral is valid down to 10 meters,
assuming that reliable a priori substrate albedo is available. Water turbidity has an important effect on retrievals -
Case 2 water with small concentrations of suspended solids allows for 10% accuracy down to 10 meters over bright
targets. The retrieval accuracy is likely to improve with tighter a priori constrains, constraints obtained from the
context of entire image, or independent information from multiple stereo pairs collected in a single WV02 pass.
The Passive A-Band Wind Sounder (PAWS) was funded through NASA's Instrument
Incubator Program (IIP) to determine the feasibility of measuring tropospheric wind speed profiles
from Doppler shifts in absorption O2 A-band. It is being pursued as a low-cost and low-risk alternative
capable of providing better wind data than is currently available. The instrument concept is adapted
from the Wind Imaging Interferometer (WINDII) sensor on the Upper Atmosphere Research Satellite.
The operational concept for PAWS is to view an atmospheric limb over an altitude range from the
surface to 20 km with a Doppler interferometer in a sun-synchronous low-earth orbit. Two orthogonal
views of the same sampling volume will be used to resolve horizontal winds from measured line-of-sight
A breadboard instrument was developed to demonstrate the measurement approach and to
optimize the design parameters for the subsequent engineering unit and future flight sensor. The
breadboard instrument consists of a telescope, collimator, filter assembly, and Michelson
interferometer. The instrument design is guided by a retrieval model, which helps to optimize key
parameters, spectral filter and optical path difference in particular.
An instrument concept for an Imaging Multi-Order Fabry-Perot Spectrometer (IMOFPS) has been developed for measuring tropospheric carbon monoxide (CO) from space. The concept is based upon a correlation technique similar in nature to multi-order Fabry-Perot (FP) interferometer or gas filter radiometer techniques, which simultaneously measure atmospheric emission from several infrared vibration-rotation lines of CO. Correlation techniques provide a multiplex advantage for increased throughput, high spectral resolution and selectivity necessary for profiling tropospheric CO. Use of unconventional multilayer interference filter designs leads to improvement in CO spectral line correlation compared with the traditional FP multi-order technique, approaching the theoretical performance of gas filter correlation radiometry. In this implementation, however, the gas cell is replaced with a simple, robust solid interference filter. In addition to measuring CO, the correlation filter technique can be applied to measurements of other important gases such as carbon dioxide, nitrous oxide and methane. Imaging the scene onto a 2-D detector array enables a limited range of
spectral sampling owing to the field-angle dependence of the filter transmission function. An innovative anamorphic optical system provides a relatively large instrument field-of-view for imaging along the orthogonal direction across the detector array. An important advantage of the IMOFPS concept is that it is a small, low mass and high spectral resolution spectrometer having no moving parts. A small, correlation spectrometer like IMOFPS would be well suited for global observations of CO2, CO, and CH4 from low Earth or regional observations from Geostationary orbit. A prototype instrument is in development for flight demonstration on an airborne platform with potential applications to atmospheric chemistry, wild fire and biomass burning, and chemical dispersion monitoring.