Steven P. Brumby, Neal R. Harvey, Simon Perkins, Reid B. Porter, John J. Szymanski, James Theiler, ...
genetic algorithm for combining new and existing image
Neal R. Harvey, Steven P. Brumby, Simon J. Perkins, Reid B. Porter, James Theiler, A. Cody Young, ...
image processing tools for multispectral imagery
Miriam Leeser, James Theiler, Michael Estlick, Natasha Kitaryeva, John J. Szymanski
We investigate the effect of truncating the precision of hyperspectral image data for the purpose of more efficiently segmenting the image using a variant of k-means clustering. We describe the...
Advanced Processing for High-bandwidth Sensor Systems (2007)
John J. Szymanski, P. Blain, J. Bloch, C. Brislawn, S. Brumby, M. Caffrey, ...
Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of...
Steven P. Brumby, Neal R. Harvey, Jeffrey J. Bloch, James Theiler, Simon Perkins, A. Cody Young, ...
header for SPIE use
Neal R. Harvey, Steven P. Brumby, Simon J. Perkins, Reid B. Porter, James Theiler, A. Cody Young, ...
evolution of image processing tools for multispectral imagery
Advanced Processing for High-bandwidth Sensor Systems (2007)
John J. Szymanski, P. Blain, J. Bloch, C. Brislawn, S. Brumby, M. Caffrey, ...
Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of...
Miriam Leeser, Pavle Belanovic, Michael Estlick, John J. Szymanski, James Theiler
Unsupervised clustering is a powerful technique for processing multispectral and hyperspectral images. Last year, we reported on an implementation of k-means clustering for multispectral images. Our...
Steven P. Brumby, James Theiler, Jeffrey J. Bloch, Neal R. Harvey, Simon Perkins, John J. Szymanski, ...
header for SPIE use
Neal R. Harvey, Steven P. Brumby, Simon Perkins, James Theiler, John J. Szymanski, J. Bloch, ...
Abstract — We have developed an automated feature detection/classification system, called Genie (GENetic Imagery Exploitation), which has been designed to generate image processing pipelines for a...
Automated Simultaneous Multiple Feature Classification of MTI Data (2002)
Neal Harvey James, James Theiler, Lee Balick, Paul Pope, John J. Szymanski, Simon J. Perkins, ...
Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the twoclass problem of detecting a single feature against a background of non-feature. In addition...
Neal R. Harvey, James Theiler, Steven P. Brumby, Simon Perkins, John J. Szymanski, Jeffrey J. Bloch, ...
We have developed an automated feature detection /classification system, called GENetic Imagery Exploitation (GENIE), which has been designed to generate image processing pipelines for a variety of...
Co-design of Software and Hardware to Implement Remote Sensing Algorithms (2001)
James Theiler, Jan Frigo, Maya Gokhale, John J. Szymanski
Both for o#ine searches through large data archives and for onboard computation at the sensor head, there is a growing need for ever-more rapid processing of remote sensing data. For many algorithms...
Using blocks of skewers for faster computation of pixel purity index (2000)
James Theiler, Dominique D. Lavenier, Neal R. Harvey, Simon J. Perkins, John J. Szymanski
The "pixel purity index " (PPI) algorithm proposed by Boardman, et al.
GENIE: A Hybrid Genetic Algorithm for Feature Classification (2000)
Simon Perkins, James Theiler, Steven P. Brumby, Neal R. Harvey, Reid Porter, John J. Szymanski, ...
We consider the problem of pixel-by-pixel classification of a multi-spectral image using supervised learning. Conventional supervised classification techniques such as maximiun likelihood...
Finding golf courses: The ultra high tech approach (2000)
Neal R. Harvey, Simon Perkins, Steven P. Brumby, James Theiler, Reid B. Porter, A. Cody Young, ...
Abstract. The search for a suitable golf course is a very important issue in the travel plans of any modern manager. Modern management is also infamous for its penchant for high-tech gadgetry. Here...
Using Blocks of Skewers for Faster Computation of Pixel Purity Index (2000)
James Theiler, Dominique D. Lavenier, Neal R. Harvey, Simon J. Perkins, John J. Szymanski
The \pixel purity index" (PPI) algorithm proposed by Boardman, et al. 1 identi es potential endmember pixels in multispectral imagery. The algorithm generates a large number of \skewers"...
Design Tradeoffs in a Hardware Implementation of the k-Means Clustering Algorithm (2000)
Miriam Leeser, James Theiler, Michael Estlick, John J. Szymanski
Hyperspectral imagery provides exquisitely detailed information, but poses a serious challenge to the image analyst. Massive quantities of data must be reduced in a way that identifies useful...
Using blocks of skewers for faster computation of Pixel Purity Index (2000)
James Theiler Dominique, Dominique D. Lavenier, Neal R. Harvey, Simon J. Perkins, John J. Szymanski
The \pixel purity index" (PPI) algorithm proposed by Boardman, et al. 1 identies potential endmember pixels in multispectral imagery. The algorithm generates a large number of \skewers"...
James Theiler, Miriam Leeser, Michael Estlick, John J. Szymanski
Modern hyperspectral imagers can produce data cubes with hundreds of spectral channels and millions of pixels. One way to cope with this massive volume is to organize the data so that pixels with...
Evolving retrieval algorithms with a genetic programming scheme (1999)
James Theiler, Neal R. Harvey, Steven P. Brumby, John J. Szymanski, Steven Alferink, Simon Perkins, ...
The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that...
Investigation of Image Feature Extraction by a Genetic Algorithm (1999)
Steven P. Brumby, James Theiler, Simon J. Perkins, Neal Harvey, John J. Szymanski, Jeffrey J. Bloch, ...
We describe the implementation and performance of a genetic algorithm (GA) which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive...