Showing papers on "VNIR published in 2000"

Method for determination of analytes using near infrared, adjacent visible spectrum and an array of longer near infrared wavelengths

Abstract: Described is a method which uses spectral data simultaneously collected in a continuous array of discrete wavelength points of the visible spectrum adjacent to the infrared and near infrared part of the light spectrum. The spectral data is collected using a number of detectors with different sensitivity ranges. Some detectors may be sensitive to visible and, possibly, to part of the near infrared portion of radiation. Spectral data from the infrared spectrum is collected with the infrared detectors, and are in some embodiments insensitive to the visible light.

Estimating surface fluxes over the SGP site with remotely sensed data

Abstract: The estimation of surface energy fluxes using remotely sensed data requires the combination of data from several sources, including land use, vegetation cover and surface temperature. Land use and vegetation cover were obtained from visible and near infrared (VNIR) data, while the state variable, surface temperature, was obtained from thermal infrared (TIR) data. An approach to combine these data with an energy balance model was studied as part of the 1997 Southern Great Plains Experiment (SGP97). Toward this end, VNIR and TIR images for 2 July 1997 were analyzed over the El Reno, Oklahoma (OK) site using data from the Thermal Infrared Multispectral Scanner (TIMS) and Thematic Mapper Simulator (TMS) airborne instruments. Intensive ground measurements constrained leaf area indices, canopy height and surface meteorological inputs required by the model. The observed brightness temperatures, when corrected for atmospheric effects using MODTRAN, nearby radiosoundings and the temperature-emissivity separation (TES) algorithm, were mostly within VC of ground based temperatures. The resulting surface temperatures were used in a two-source model that considers the heat flux and temperature contributions from the soil and vegetation. The heat flux predictions on average agree within 50 W m−2 of tower-based observations.

Surveillance camera system with infrared and visible light bandpass control circuit

Abstract: A camera system switches electronically between infrared radiation sensing and visible light sensing depending on ambient conditions, to optimize visible picture quality for surveillance. An electronic CCD camera has an optical bandpass filter having a stop band between the infrared radiation spectrum and the visible light spectrum to provide high quality visible light images when not in the infrared mode and high quality mono infrared images when not in visible light mode. A control circuit compares the camera signal with a photocell signal and controls the camera's sensing mode and an if illuminator's operation in accordance with the ambient conditions.

Applications of Orbital Imaging Radar for Geologic Studies in Arid Regions: The Saharan Testimony

Abstract: The multi-frequency and multi-polarization Shuttle Imaging Radar (SIR)-C/X Synthetic Aperture Radar (SAR) data collected in 1994 aboard two flights of the Shuttle Endeavour constitute a milestone in imaging of deserts from space. The data are here used to explore the eastern Saham, including lithological and structural mapping, geomorphological studies, and mineral exploration. The SIR-C/X-SAR images in this environment are generally found to be (1) less useful for lithological mapping than orbital visible and near infrared (VNLA) images, except where rock types weather differently to produce varying roughness levels; (2) superior to orbital vm images for structural mapping in areas of subdued relief or where structures are partially covered by dry sand, as well as in tectonically active mountainous terrains; (3) superior to orbital VNIR images for mapping sugace and sub-sugace geomorphological features such as paleo-channels; and (4) useful in delineating geologic controls on mineral deposits, but inferior to orbital VNIR images for direct identification of these.

Feasibility of optical detection of land mine trip wires

Abstract: Research to assess the feasibility of developing a standoff active or passive optical tripwire detector is discussed. Reflectives of typical tripwires and background materials were measured for UV, VNIR and SWIR wavelengths. A breadboard testbed was developed to obtain images of tripwires against various backgrounds for various geometries and a wide range of VU and VNIR wavelengths. Sample images of simulated and real tripwires in uncluttered environments and against typical cluttered backgrounds were acquired and analyzed. Line detection algorithms were applied to the images to detect tripwires. Although detection was not attempted in real-time, analysis showed that available, cost-effective DSPs could potentially execute those algorithms on the images in real-time. The algorithms successfully detected tripwires in a heavily cluttered background and even have the capability to detect partially obscured wires. To complement the measurements, a spreadsheet model was developed to evaluate the merits of different detectors, sources of illumination, wavebands and geometries for different scenarios. Acceptable signal-to- clutter ratios were found for a number of reasonable passive and active illumination scenarios. The study demonstrated that an optical tripwire detector is feasible in principle.

Comprehensive hyperspectral system simulation: II. Hyperspectral sensor simulation and premliminary VNIR testing results

Abstract: An end-to-end hyperspectral system model with applications to space and airborne sensor platforms is under development and testing. In this paper we discuss current work in the development of the sensor model and the results of preliminary testing. It is capable of simulating collected hyperspectral imagery of the ground as sensors operating from space or airborne platforms would acquire it. Dispersive hyperspectral imaging sensors operating from the visible through the thermal infrared spectral regions can be modeled with actual hyperspectral imagery or simulated hyperspectral scenes used as inputs. In the sensor model portion, fore-optics (misalignment), dispersive spectrometer designs, degradations (platform motion, smile, keystone, misregistration), focal plane array (temperature drift, nonuniformity/nonlinearity), noise (shot, dark, Johnson, 1/f, RMS read, excess low frequency), analog-to-digital conversion, digital processing, and radiometric/temporal/wavelength calibration effects are included. The overall model includes a variety of processing algorithms including constant false alarm rate anomaly detection, spectral clustering of backgrounds for anomaly detection, atmospheric compensation, and pairwise adaptive linear matching for detection and classification. Results of preliminary testing using synthetic scene data in the visible/near infrared portion of the spectrum are discussed. Potential applications for this modeling capability include processing results performance prediction and sensor parameter specification trade studies.

An airborne multi‐angle TIR/VNIR imaging system

Abstract: The airborne multi‐angle TIR/VNIR imaging system (AMTIS) is a program to build and operate a prototype three‐channel multi‐angle imaging system. Scheduled to be operating before the end of year 2000. AMTIS will work in three scanning modes, viewing a target at least nine programmable directions. It will provide high quality data in visible/near infrared and thermal infrared spectral bands for use in deriving geophysical parameters, such as bidirectional reflectance factors. The current status of the system under construction and plans for its operation are reviewed.

Detection of narrow open-water channels from JERS-1 SAR images of Amazon forests

Abstract: We have developed a new, fully automatic method for detecting and visualizing narrow open-water rivers from 3- look JERS-1 SAR images of Amazon rainforests. We expect this method to become an operational tool for detecting river water levels in remote tropical rainforests for the purposes of environmental and disaster monitoring. To demonstrate its use, we apply this method to eight continuous and one isolated Amazon scene. The resulting approximate range of waterways corresponds highly with those seen in JERS-1 VNIR image data observed one week later in cloud-free areas. Estimates from the optical JERS-1 VNIR images give the minimum detectable width of those visualized rivers to be approximately 20 m. The brightness of the river can be used to estimate the width of the fiver from approximately 20m to approximately 150m. In wider rivers, dark areas become predominant.

Image fusion of high resolution LWIR and IITV sensors for pilotage

Abstract: Infrared, image intensified and low light level CCD sensors have well recognized uses, capabilities and limitations. Several government and industry studies objectively evaluated the relative merits of these sensors as applied to day and night pilotage missions. These studies found that each sensor excelled under different conditions and environments. Most pilots preferred having at least two different types of sensors available, since they sometimes complement each other. The ultimate goal of image fusion is to provide an automated method integrating the various image information from different sensors to yield a high quality real time presentation. Ideally, such a composite should retain the essential information from each sensor while minimizing any artifacts or distortions, so that the end result is a seamless representation of reality. By putting together several technologies, image fusion offers an overall improved single image representation of thermal, visible and color, etc. Raytheon has developed image fusion algorithms for fusing high sensitivity/resolution sensors for both the long-wave infrared (LWIR) and the visible-near infrared (VNIR) spectral regions. The algorithms are implemented in real time processing hardware and have been demonstrated in various aircraft, including helicopters. The imagery from the two respective spectral bands is fused via digital image processing techniques so that the information content is optimized for a variety of daytime and nighttime scenes. Imagery from these demonstrations shows dramatic improvement in situational awareness for pilotage.

Active hyperspectral imaging

Abstract: Hyperspectral imaging has emerged as a useful technology for target recognition and anomaly detection However, passive hyperspectral sensors in the VNIR/SWIR are limited to daytime and fair weather operations Furthermore, for applications such as material identification, the need for reflectance spectra requires either inscene calibration panels or detailed atmospheric information Active hyperspectral sensing has the potential to increase the utility of hyperspectral imaging by enabling nighttime operation and non-cooperative conversion to reflectance At MIT Lincoln Laboratory we have developed an active hyperspectral sensor system to investigate combining active illumination with hyperspectral imaging Our primary illumination source is a novel broadband ‘white light’ laser, developed at MIT Lincoln Laboratory Initial phenomenology measurements have revealed an additional benefit of active illumination - enhanced scene contrast due to shadow reduction We have demonstrated two orders of magnitude decrease in false alarm rates with active illumination versus passive

Target detection and scene classification with VNIR/SWIR spectral imagery

Abstract: : Spectral imagery provides a new resource in remote sensing, which can be used for defeating camouflage, concealment and detection, as well as terrain categorization. A new sensor, the Night Vision Imaging Spectrometer (NVIS), provides VNIR/SWIR (0.4-2.5 m) spectra, which are used to here to study such applications. NVIS has a nominal GSD of 0.5- 1.5 meters in operational modes utilized for this work, which make the data well suited for studying mapping and classification algorithms. Data taken at Pt. A.P. Hill on April 29, 2000 are studied here. A Principal Components Transformation was performed on the NVIS data. From this new data set, target spectra were collected for use in classification algorithms. The NVIS data was converted from radiance to reflectance in two different ways: Empirical Line Method and Internal Average Relative Reflectance. Using this data, various standard algorithms were performed. It was found that while none of the algorithms correctly classified all of the selected targets, the Mahalanobis Distance and Mixture Tuned Matched Filter(TM) algorithms were the most successful.