KEYWORDS: Clouds, Image segmentation, Prototyping, Image classification, Infrared imaging, Long wavelength infrared, Signal to noise ratio, Satellites, Thermography, Algorithm development
This paper reports on a novel approach to atmospheric cloud segmentation from a space based multi-spectral pushbroom satellite system. The satellite collects 15 spectral bands ranging from visible, 0.45 um, to long wave infa-red (IR), 10.7um. The images are radiometrically calibrated and have ground sample distances (GSD) of 5 meters for visible to very near IR bands and a GSD of 20 meters for near IR to long wave IR. The algorithm consists of a hybrid-classification system in the sense that supervised and unsupervised networks are used in conjunction. For performance evaluation, a series of numerical comparisons to human derived cloud borders were performed. A set of 33 scenes were selected to represent various climate zones with different land cover from around the world. The algorithm consisted of the following. Band separation was performed to find the band combinations which form significant separation between cloud and background classes. The potential bands are fed into a K-Means clustering algorithm in order to identify areas in the image which have similar centroids. Each cluster is then compared to the cloud and background prototypes using the Jeffries-Matusita distance. A minimum distance is found and each unknown cluster is assigned to their appropriate prototype. A classification rate of 88% was found when using one short wave IR band and one mid-wave IR band. Past investigators have reported segmentation accuracies ranging from 67% to 80%, many of which require human intervention. A sensitivity of 75% and specificity of 90% were reported as well.
A familiar concept in imaging spectrometry is that of the three dimensional data cube, with one spectral and two spatial dimensions. However, available detectors have at most two dimensions, which generally leads to the introduction of either scanning or multiplexing techniques for imaging spectrometers. For situations in which noise increases less rapidly than as the square root of the signal, multiplexing techniques have the potential to provide superior signal-to-noise ratios. This paper presents a theoretical description and numerical simulations for a new and simple type of Hadamard transform multiplexed imaging spectrometer. Compared to previous types of spatially encoded imaging spectrometers, it increases etendue by eliminating the need for anamorphically compressed re-imaging onto the entrance aperture of a monochromator or spectrophotometer. Compared to previous types of spectrally encoded imaging spectrometers, it increases end-to-end transmittance by eliminating the need for spectral re-combining optics. These simplifications are attained by treating the pixels of a digital mirror array as virtual entrance slits and the pixels of a 2-D array detector as virtual exit slits of an imaging spectrometer, and by applying a novel signal processing technique.
Hadamard Transform Spectrometer (HTS) approaches share the multiplexing advantages found in Fourier transform spectrometers. Interest in Hadamard systems has been limited due to data storage/computational limitations and the inability to perform accurate high order masking in a reasonable amount of time. Advances in digital micro-mirror array (DMA) technology have opened the door to implementing an HTS for a variety of applications including fluorescent microscope imaging and Raman imaging. A Hadamard transform spectral imager (HTSI) for remote sensing offers a variety of unique capabilities in one package such as variable spectral and temporal resolution, no moving parts (other than the micro-mirrors) and vibrational insensitivity. An HTSI for remote sensing using a Texas Instrument digital micro-mirror device (DMD) is being designed for use in the spectral region 1.25 - 2.5 micrometers . In an effort to optimize and characterize the system, an HTSI sensor system simulation has been concurrently developed. The design specifications and hardware components for the HTSI are presented together with results calculated by the HTSI simulation that include the effects of digital (vs. analog) scene data input, detector noise, DMD rejection ratios, multiple diffraction orders and multiple Hadamard mask orders.
The primary method used to determine if an unattended package is dangerous is currently transmission radiography. This system has two main drawbacks. First, the film must be placed on one side of the package and an x-ray source on the other side of the package. An arrangement that cannot always be achieved due to the position of the package. The other drawback is that the package may detonate before the film is removed and all the information about the package lost.
The implementation of a backscattered x-ray landmine detection system has been demonstrated in laboratories at both Sandia National Laboratories (SNL) and the University of Florida (UF). The next step was to evaluate the modality by assembling a system for fieldwork and to evaluate the systems performance with real laboratories. To assess the system's response to a variety of objects, buried simulated plastic and metal antitank landmines, surface simulated plastic antipersonnel landmines, and surface metal fragments were used as targets for the field test. The location of the test site was an unprepared field at SNL. The tests conducted using real landmines were held at UF using various burial depths. The field tests yielded the same levels of discrimination between soil and landmines that had been detected in laboratory experiments. The tests on the real landmines showed that the simulated landmines were a good approximation. The real landmines also contained internal features that would allow not only the detection of the landmines, but also the identification of them.
Currently the most common method to determine the contents of a package suspected of containing an explosive device is to use transmission radiography. This technique requires that an x-ray source and film be placed on opposite sites of the package. This poses a problem if the package is placed so that only one side is accessible, such as against a wall. There is also a threat to personnel and property since explosive devices may be 'booby trapped.' We have developed a method to x-ray a package using backscattered x-rays. This procedure eliminates the use of film behind the target. All of the detection is done from the same side as the source. When an object is subjected to x-rays, some of them are scattered back toward the source. The backscattering of x-rays is proportional to the atomic number (Z) of the material raised to the 4.1 power. This Z4.1 dependence allows us to easily distinguish between explosives, wires, timer, batteries, and other bomb components. Backscatter experiments at Sandia National Laboratories have been conducted on mock bombs in packages. We are able to readily identify the bomb components. The images that are obtained in this procedure are done in real time and the image is displayed on a computer screen.
Numerous active landmines buried around the world have prompted work on various technologies for locating these mines. One promising technique directs a beam of x-rays into the ground, and detects the fraction scattered back. An image of the detected photons reveals the subsurface content. In this experiment, the effect of photon cross-talk between adjacent x-ray beam/photon detector systems was investigated. If feasible, multiple beam/detector systems would allow a single landmine detection system to survey the ground much faster. The results of the examination of the segmented detector system showed that this system is quite capable of producing very recognizable images of surface buried landmines, in spite of significant limitations imposed by the required setup of this particular experiment. Therefore, the segmented detector system is an option that should be strongly investigated in the development of a landmine detector system if there is a critical emphasis on speed.
The implementation of a backscattered x-ray landmine detection system has been demonstrated in laboratories at both Sandia National Laboratories (SNL) and the University of Florida (UF). The next step was to evaluate the modality by assembling a system for field work. To assess the system's response to a variety of objects, buried plastic and metal antitank landmines, surface plastic antipersonnel landmines, and surface metal fragments were used as targets. The location of the test site was an unprepared field at SNL. The x-ray machine used for the outside landmine detection system was a Philips industrial x-ray machine, model MCN 225, which was operated at 150 kV and 5 mA and collimated to create a 2 cm diameter x-ray spot on the soil. The detectors used were two BICRON plastic scintillation detectors: one collimated (30 cm X 30 cm active area) to respond primarily to photons that have undergone multiple collision and the other uncollimated (30 cm X 7.6 cm active area) to respond primarily to photons that have had only one collision. To provide motion, the system was mounted on a gantry and rastered side-to-side using a computer-controlled stepper motor with a come-along providing the forward movement. Data generated from the detector responses were then analyzed to provide the images and locations of landmines. Changing from the lab environment to the field did not decrease the system's ability to detect buried or obscured landmines. The addition of rain, blowing dust, rocky soil and native plant-life did not lower the system's resolution or contrast for the plastic or the metal landmines.
A continuously operating, scanning x-ray machine is being developed or landmine detection using backscattered x-rays. The source operates at 130 kV and 650 mA. The x-rays are formed by electrons striking a high Z target. Target shape is an approximate 5 cm wide by 210 cm long racetrack. The electron beam is scanned across this target with electromagnets. There are 105, 1-cm by 1-cm collimators in each leg of the racetrack for a total of 210 collimators. The source is moved in the forward direction at 3 mi/h. The forward velocity and collimator spacing are such that a grid of collimated x-rays are projected at normal incidence to the soil.T he spacing between the collimators and the ground results in a 2-cm by 2-cm x-ray pixel on the ground. A unique detector arrangement of collimated and uncollimated detectors allows surface features to be recognized and removed, leaving an image of a buried landmine. Another detector monitors the uncollimated x-ray output and is used to normalize the source output. The mine detector is being prepared for an advanced technology demonstration (ATD). The ATD is scheduled for midyear of 1998. The results of the source performance in pre ATD tests will be presented.
Lateral migration radiography (LMR), a form of Compton backscatter radiography, is applied to the detection and identification of landmines. The LMR system consists of two inner uncollimated detectors positioned to optimally detect first scattered photons and two outer collimated detectors designed to detect primarily photons that have had two or more scatterings. The difference between the collimated and uncollimated detector response to both the landmines themselves and the different types of landmine image masking phenomena, form the basis of the image enhancement and landmine identification procedures. Surface feature information is the primary component of the uncollimated detector response. The collimated detector signal contains information about the surface features as well as the buried objects. The principles of the detection system have been shown in previous work and now the focus has shifted to the preparation for field tests and the associated problems. One of the expected events that the detector system will encounter is the variation of detector height with respect to the ground. This is caused by irregularities in the surface as will as oscillations of the detection vehicle. The collimated detectors and the uncollimated detector react differently to height variations. When the detector height increases the uncollimated detector response will be reduced due to the decrease in solid angle. Although the collimated detector will also be affected by the change in solid angle the dominate reaction is the loss of collimation causing the collimated detectors signal to increase. When the detector height decreases the opposite responses are observed. By using the information from both detector systems, the effects of the detector height variation can be removed.
The Compton Backscatter Imaging (CBI) technique has been applied successfully to detect buried plastic anti-tank landmines. The images acquired by a CBI system are often cluttered by surface features. Additionally, some buried objects give the same response as the plastic landmines. The landmine detection can be successful only when the detection system is capable of distinguishing between surface features and the mine-like objects. This can be accomplished by designing detectors that differentiate between the surface features and the buried objects. An understanding of the physical phenomena underlining the CB image formation helps us to design these detectors. To study the physics of the Compton backscattering, the photon transport in a CBI system is simulated using Monte-Carlo calculations with the generalized particle transport program MCNP. The photon tracks are graphically displayed using a visualization program SABRINA. On the basis of the results from these Monte-Carlo analyses, a four-detector system has been designed. This detector design utilizes the unique nature of various collision components of the scattered photons to generate separate images of buried objects and surface features. The success of this detector design is demonstrated through a series of analytically generated images. The results of the experimental measurements that validate these analytical predictions are brought out in a separate paper to be presented in this conference.
The measurement and removal of noise from images created using lateral migration backscatter radiography (LMBR) a form of Compton backscatter imaging (CBI) is applied to the detection and identification of landmines. The photons that interact with the landmine produce the signal component of interest. The signal is corrupted by both quantum and structured noise. The structured noise is due to photon interaction with non-mine material. Due to the strong response of all detectors to soil surface features and other buried objects, image enhancement methods are essential for landmine identification. A four detector system is used to generate the LMBR/CB images. The inner two detectors are uncollimated and positioned to optimally detect first scattered photons. The outer detectors are collimated to detect photons that have had two or more scatterings. The difference between the collimated and uncollimated detector responses to the different types of landmine image masking phenomena, form the basis of the image enhancement and landmine identification procedures. The surface feature information is obtained by the uncollimated detectors. The collimated detector signal contains information about the surface features as well as the buried objects. Using images from these two sets of detectors the surface objects can be analyzed for possible landmines and then removed. The buried objects can then be resolved. The measurements and image enhancements demonstrate that it is possible to detect 12' plastic landmines at a buried of 3' under simulated battlefield conditions.
KEYWORDS: Sensors, Collimation, Land mines, Mining, Detection and tracking algorithms, Image sensors, Data acquisition, Imaging systems, Backscatter, Control systems
Earlier landmine imaging systems used two collimated detectors to image objects. These systems had difficulty in distinguishing between surface features and buried features. Using a combination of collimated and uncollimated detectors in a Compton backscatter imaging (CBI) system, allows the identification of surface and buried features. Images created from the collimated detectors contain information about the surface and the buried features, while the uncollimated detectors respond (approximately 80%) to features on the surface. The analysis of surface features are performed first, then these features can be removed and the buried features can be identified. Separation of the surface and buried features permits the use of a globbing algorithm to define regions of interest that can then be quantified [area, Y dimension, X dimension, and center location (xo, yo)]. Mine composition analysis is also possible because of the properties of the four detector system. Distinguishing between a pothole and a mine, that was previously very difficult, can now be easily accomplished.
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