Collaboration between Exelis Geospatial Systems with University of Rochester and Rochester Institute of Technology aims to develop an active THz imaging focal plane array utilizing 0.35um CMOS MOSFET technique. An appropriate antenna is needed to couple incident THz radiation to the detector which is much smaller than the wavelength of interest. This paper simply summarizes our work on modeling the optical characteristics of bowtie antennae to optimize the design for detection of radiation centered on the atmospheric window at 215GHz. The simulations make use of the finite difference time domain method, calculating the transmission/absorption responses of the antenna-coupled detector.
The effectiveness of a power generation site's cooling pond has a significant impact on the overall efficiency of a
power plant. The ability to monitor a cooling pond using thermal remote sensing, coupled with hydrodynamic
models, is a valuable tool for determining the driving characteristics of a cooling system. However, the thermodynamic
analysis of a cooling lake can become significantly more complex when a power generation site is located
in a northern climate. The heated effluent from a power plant entering a cooling lake is often not enough to keep
a lake from freezing during winter months. Once the lake is partially or fully frozen, the predictive capabilities
of the hydrodynamic model are weakened due to an insulating surface layer of ice and snow. Thermal imagery
of a cooling pond was collected over a period of approximately 16 weeks in tandem with high-density thermal
measurements both in open water and embedded in ice, meteorological data, and snow layer characterization
data. The proposed research presents a method to employ thermal imagery to improve the performance of a 3-D
hydrodynamic model of a power plant cooling pond in the presence of ice and snow.
Accurate retrieval of wildland fire temperature from remote imagery would be useful in improving prediction of fire propagation and estimates of fire effects such as burn severity and gas and particle production. The feasibility of estimating temperatures for subpixel fires by spectral unmixing has been established by previous work with
the AVIRIS sensor. However, this unmixing approach can also produce optimizations for temperatures that may not be physically related to the fraction of flaming combustion in a pixel. Furthermore, previous techniques have treated fire as a blackbody and have modeled the mixed pixel transmitted radiance as two blackbody sources. This first order approximation can also affect the temperature retrieval. Knowledge of emissivity and use of a more complex radiance model should improve the accuracy of the temperature estimation. We therefore, propose a technique which improves the previous approach by using the potassium emission to pre-determine pixels that actually contain signal from flaming combustion and a modified mixed pixel radiance model. A non-linear, constrained multi-dimensional optimization procedure which estimates flame emissivity was applied
to the model to estimate fire temperature and its areal extent. Results are shown for AVIRIS data sets acquired over Cuiaba, Brazil (1995) and the San Bernardino Mountains (1999).
The purpose of this paper is to describe a physics based fire model in DIRSIG. The main objective is to utilize research on radiative emissions from fire to create a 3D rendering of a scene to generate a synthetic multispectral or hyperspectral image of wildfire. These synthetic images can be used to evaluate detection algorithms and sensor platforms.
To produce realistic flame structures and realistic spectral emission across the visible and infrared spectrum, we first need to produce 3D time-dependent data describing the fire evolution and its interaction with the environment. Here we utilize an existing coupled atmosphere-fire model to represent the finescale dynamics of convective processes in a wildland fire. Then the grid-based output from the fire propagation model can be used in DIRSIG along with the spectral emission representative of a wildland fire to run the ray-tracing model to create the synthetic scene.
The technical approach is based on a solid understanding of user requirements for format and distribution of the information provided by a high spatial resolution remote sensing system.
Typical existing fire detection algorithms for airborne and satellite based imagers employ the Planckian radiation in the 3.5 -5 μm and 8 - 14 μm spectral regions. These algorithms can have high false alarm rates and furthermore, the issue of validation of subpixel detection is a lingering problem. We present an empirical testing of fire detection algorithms for controlled and uniform burning and hot targets of known area. Image data sets of the targets were captured at different altitudes with the Modular Imaging Spectrometer Instrument (MISI). MISI captures hyperspectral
VNIR and multispectral SWIR/MWIR/LWIR imagery. The known range of target areas ranges from larger than the MISI IFOV to less than 0.5% of the IFOV. The in situ temperatures were monitored with thermocouples and pyrometers. Spectroradiometric data of targets and backgrounds were also collected during the experiment. The data were analysed using existing algorithms as well as novel approaches. The algorithms are compared by determining the minimum resolvable
fire pixel fraction.
Fire detection has been an active research field for many years and a number of algorithms have been proposed. These algorithms, however, are often inflexible in dealing with the spatial and temporal heterogeneity of the environment. Different biomes, seasons, and temperatures usually cause the performance of these algorithms to vary dramatically. In this paper, we propose a new algorithm for fire detection based on the Mahalanobis distance that exploits the statistical properties of multi-spectral images. The distinguishing feature of our algorithm is its robustness. It can effectively differentiate fire from background in various environments, using a single, fixed threshold. We evaluate our algorithm by comparing it to three state-of-the-art existing algorithms: the MODVOLC normalized fire index algorithm, the Arino's threshold algorithm, and the contextual MODIS algorithm. All algorithms are tested using MODIS images taken in different parts of the world as well as at different times. Experimental results demonstrate that our algorithm consistently achieves the best performance, showing a low and constant false alarm rate.
In consumer digital cameras, some of the primary tasks in the image capture data path include automatic focus, automatic exposure determination and auto-white balance (AWB). There are numerous algorithms used in implementing these tasks--auto-focus is implemented using maximum contrast, ranging or sonar; white balance using color gamut determinations and `gray value estimations', and auto- exposure using scene evaluations. We evaluate the system implications of implementing one of these tasks, namely white balance on an embedded system--a digital camera. There include, among other things, design approach, power consumption, software vs. hardware implementation and microprocessor vs. ASIC implementation. Commercially available digital cameras and their choice of AWB implementation are discussed where appropriate. Such an evaluation will assist, we hope, anyone designing or building a digital camera sub-system.
In consumer digital cameras, some of the primary tasks in the image capture data path include automatic focus, automatic auto-focus is implemented using maximum contrast, ranging or sonar; white balance using color gamut determinations and 'gray value estimations', and auto- exposure using scene evaluations. We evaluate the system implications of implementing one of these task, namely auto- exposure on an embedded system - a digital camera. These include, among other things, design approach, power consumption, leverage from film cameras, and component count. Commercially available digital cameras and their choice of AE implementation are discussed where appropriate. Such an evaluation will assist, we hope, anyone designing or building a digital camera sub-system.