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Digitized historic film data were used to model the fireball of a nuclear detonation and simulate the sensor response within the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Historic films were used to determine the temperature and dimensions of the nuclear fireball and create an input to DIRSIG. DIRSIG was used to analyze how environmental interactions change the optical signal...
As technology advances; blur in an image remains as an ever-present issue in the image processing field. A blurred image is mathematically expressed as a convolution of a blur function with a sharp image, plus noise. Removing blur from an image has been widely researched and is still important as new images are collected. Without a reference image, identifying, measuring, and removing blur from a...
Generalized Fourier series with orthogonal polynomial bases have useful applications in several fields, including pattern recognition and image and signal processing. However, computing the generalized Fourier series can be a challenging problem, even for relatively well behaved functions. In this paper, a method for approximating a sparse collection of Fourierlike coefficients is presented that uses...
Polarimetric and hyperspectral imaging are two of the most frequently used remote sensing modalities. While extensive work has been done in both fields independently, relatively little work has been done using both in conjunction with one another. Combining these two common remote sensing techniques, we hope to estimate index of refraction, without a priori knoweledge of local weather conditions or...
Correlative interferometric image reconstruction is a computational imaging approach for synthesizing images from sensor arrays and relies on estimating source intensity from the cross-correlation across near-field or far-field measurements from multiple sensors of the arrays. Key to using the approach is the exploitation of relationship between the correlation and the source intensity. This relationship...
The use of cone-beam computed tomography (CBCT) in medical field can help the clinicians to visualize the hard tissues in head and neck region via a cylindrical field of view (FOV). The images are usually presented with reconstructed three-dimensional (3D) imaging and its orthogonal (x-, y- and z-planes) images. Spatial relationship of the structures in these orthogonal views is important for diagnosis...
Researchers at Lawrence Livermore National Laboratory (LLNL) have started digitizing technical films spanning the above ground atmospheric nuclear testing operations conducted by the United States from 1950 through the 1960s. This technical film test data represents unique information that can be use as a primary validation data source for nuclear effects codes that are used by national researchers...
Structure-from-Motion (SfM) applications attempt to reconstruct the three-dimensional (3D) geometry of an underlying scene from a collection of images, taken from various camera viewpoints. Traditional optimization techniques in SfM, which compute and refine camera poses and 3D structure, rely only on feature tracks, or sets of corresponding pixels, generated from color (RGB) images. With the abundance...
Baseline radiation background is almost never known and constantly changes particularly in urban areas. It is difficult to know what the expected background radiation should be and how a radiological incident may elevate the radiation. Naturally occurring radiation from rocks and building materials often contributes significantly to measured radiation. Buildings and other tall structures also shield...
A strong emphasis has been made on making the healthcare system and the diagnostic procedure more efficient. In this paper, we present an automatic detection technique designed to segment out abnormalities in X-ray imagery. Utilizing the proposed algorithm allows radiologists and their assistants to more effectively sort and analyze large amount of imagery. In radiology, X-ray beams are used to detect...
Image quality is affected by two predominant factors, noise and blur. Blur typically manifests itself as a smoothing of edges, and can be described as the convolution of an image with an unknown blur kernel. The inverse of convolution is deconvolution, a difficult process even in the absence of noise, which aims to recover the true image. Removing blur from an image has two stages: identifying or...
Human activity detection from videos is very challenging, and has got numerous applications in sports evalution, video surveillance, elder/child care, etc. In this research, a model using sparse representation is presented for the human activity detection from the video data. This is done using a linear combination of atoms from a dictionary and a sparse coefficient matrix. The dictionary is created...
Exact probabilistic inference is computationally intractable in general probabilistic graph-based models, such as Markov Random Fields and Conditional Random Fields (CRFs). We investigate spanning tree approximations for the discriminative CRF model. We decompose the original computationally intractable grid-structured CRF model containing many cycles into a set of tractable sub-models using a set...
We introduce KWIVER, a cross-platform video exploitation framework that Kitware has begun releasing as open source. Kitware is utilizing a multi-tiered open-source approach to reach as wide an audience as possible. Kitware's government-funded efforts to develop critical defense technology will be released back to the defense community via Forge.mil, a government open source repository. Infrastructure,...
High bit-depth video data is becoming more common in imaging and remote sensing because higher bit-depth cameras are becoming more affordable. Displays often represent images in lower bit-depths, and human vision is not able to completely exploit this additional information in its native form. These problems are addressed with High Dynamic Range (HDR) tone mapping, which nonlinearly maps lightness...
Modern warfighters are informed by an expanding variety of Intelligence, Surveillance and Reconnaissance (ISR) sources, but the timely exploitation of this data poses a significant challenge. ObjectVideo ("OV") presents a system, Mobile ISR to facilitate ISR knowledge discovery for expeditionary warfighters. The aim is to collect, manage, and deliver time-critical information when and where...
Pointcloud registration has a number of applications in various research areas. Computational complexity and accuracy are two major concerns for a pointcloud registration algorithm. This paper proposes a novel Fast Coherent Point Drift (F-CPD) algorithm for 3D pointcloud registration. The original CPD method is very time-consuming. The situation becomes even worse when the number of points is large...
For single-modal data, object recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system where the signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a specific desired tolerance is required to perform classification and recognition optimally....
An application for video data analysis based on computer vision and machine learning methods is presented. Novel gender and age classifiers based on adaptive features, local binary patterns and support vector machines are proposed. More than 94% accuracy of viewer's gender recognition is achieved. Our age estimation algorithm provides world-quality results for MORTH database, but focused on real-life...
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