An Empirical Algorithm to Measure Soil Moisture with Imaging Radars
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soil moisture imaging radar empirical algorithm AI↗
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FPGA Coprocessor for Accelerated Classification of Images
An effort related to that described in the preceding article focuses on developing a spaceborne processing platform for fast and accurate onboard classification of image data, a critical part of modern satellite image processing. The approach again has been to exploit the versatility of recently developed hybrid Virtex-4FX field-programmable gate array (FPGA) to run diverse science applications on embedded processors while taking advantage of the reconfigurable hardware resources of the FPGAs. In this case, the FPGA serves as a coprocessor that implements legacy C-language support-vector-machine (SVM) image-classification algorithms to detect and identify natural phenomena such as flooding, volcanic eruptions, and sea-ice break-up. The FPGA provides hardware acceleration for increased onboard processing capability than previously demonstrated in software. The original C-language program demonstrated on an imaging instrument aboard the Earth Observing-1 (EO-1) satellite implements a linear-kernel SVM algorithm for classifying parts of the images as snow, water, ice, land, or cloud or unclassified. Current onboard processors, such as on EO-1, have limited computing power, extremely limited active storage capability and are no longer considered state-of-the-art. Using commercially available software that translates C-language programs into hardware description language (HDL) files, the legacy C-language program, and two newly formulated programs for a more capable expanded-linear-kernel and a more accurate polynomial-kernel SVM algorithm, have been implemented in the Virtex-4FX FPGA. In tests, the FPGA implementations have exhibited significant speedups over conventional software implementations running on general-purpose hardware.
Pingree, Paula J.↗
High-Multiplicity Muon Airshower Analysis at NOvA Far Detector
We process and analyze muon airshower data from the NOvA far detector using various image processing algorithms, such as Fast Fourier Transformation, and Hough line transformation. From the processed event images, we calculate multiple parameters for our study. We are looking for physics features, including East-West Asymmetry, anisotropies in right ascension, and seasonal variation. Additionally, we have developed an algorithm to count the multiplicity of muons in the airshower events using the single muon data.
Lima, Aklima Khanam [Syracuse U.]↗
Image processing via VLSI: A concept paper
Implementing specific image processing algorithms via very large scale integrated systems offers a potent solution to the problem of handling high data rates. Two algorithms stand out as being particularly critical -- geometric map transformation and filtering or correlation. These two functions form the basis for data calibration, registration and mosaicking. VLSI presents itself as an inexpensive ancillary function to be added to almost any general purpose computer and if the geometry and filter algorithms are implemented in VLSI, the processing rate bottleneck would be significantly relieved. A set of image processing functions that limit present systems to deal with future throughput needs, translates these functions to algorithms, implements via VLSI technology and interfaces the hardware to a general purpose digital computer is developed.
Nathan, R.↗
The Pixon Method for Data Compression Image Classification, and Image Reconstruction
As initially proposed, this program had three goals: (1) continue to develop the highly successful Pixon method for image reconstruction and support other scientist in implementing this technique for their applications; (2) develop image compression techniques based on the Pixon method; and (3) develop artificial intelligence algorithms for image classification based on the Pixon approach for simplifying neural networks. Subsequent to proposal review the scope of the program was greatly reduced and it was decided to investigate the ability of the Pixon method to provide superior restorations of images compressed with standard image compression schemes, specifically JPEG-compressed images.
Puetter, Richard↗
Passive obstacle location for rotorcraft guidance
Nap-of-the-earth flight mode is extremely demanding on the rotorcraft pilots. This fact has motivated the research in automating various components of low altitude rotorcraft flight operations. Concurrent with the development of guidance laws, efforts are under way to develop systems for locating the terrain and the obstacles using inputs from passive electrooptical sensors such as TV cameras and infrared imagers. A passive obstable location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given.
Menon, P. K. A.↗
Electro-optical navigation for aircraft
Low altitude flight is extremely demanding on the rotorcraft pilots. This fact has motivated the research in automating various components of low altitude rotorcraft flight operations. Concurrent with the development of guidance laws, efforts are underway to develop systems for locating the terrain and the obstacles using inputs from passive electro-optical sensors such as TV cameras and infrared imagers. A passive obstacle location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given.
Menon, P. K. A.↗
Truncation Of Images For Correlation
Correlation performed on relatively small computer. Proposed method for processing video images in slowly changing scenes, renditions of complicated objects truncated to points, lines, polygons, or other simplified geometrical objects. Processed by image-correlating algorithms to extract information: recognize features and to track displacements of features in subsequent image frames to determine velocities. Entails correlation of far fewer data than original images.
Shimada, Katsunori↗
Optimizing RHESSI X-ray Imaging
RHESSI X-ray imaging is possible with angular resolution as fine as 2 arcsec (FWHM) at energies from as low as 3 keV to >100 keV. However, taking full advantage of this capability has proven to be challenging given the Fourier-transform imaging technique that is used, specific instrumental considerations that must be taken into account, and the many different options of the available image reconstruction algorithms. Such considerations as the best reconstruction algorithm to use, the optimal weighting of the different Fourier components, deciding between short image integration times and rapid imaging cadence, the different energy ranges covered by the 9 detectors, the effect of pulse pile-up and albedo, etc. must all be taken into account in obtaining and interpreting RHESSI X-ray images. This poster describes different techniques for optimizing the image reconstruction depending on the science objectives - identifying compact or extended sources, searching for source motion, obtaining the best photometry, determining the believability of different features in an image, etc. The emphasis is on making full use of data from all the RHESSI detectors, including the ones behind the finest grids when warranted by the source structure. This is the case for the hard X-ray emission along the ribbons of the flare on 2005 May 13 reported by Liu et al. (2007) and this event will be used as an example.
Dennis, Brian R.↗
Effects of window size and shape on accuracy of subpixel centroid estimation of target images
A new algorithm is presented for increasing the accuracy of subpixel centroid estimation of (nearly) point target images in cases where the signal-to-noise ratio is low and the signal amplitude and shape vary from frame to frame. In the algorithm, the centroid is calculated over a data window that is matched in width to the image distribution. Fourier analysis is used to explain the dependency of the centroid estimate on the size of the data window, and simulation and experimental results are presented which demonstrate the effects of window size for two different noise models. The effects of window shape were also investigated for uniform and Gaussian-shaped windows. The new algorithm was developed to improve the dynamic range of a close-range photogrammetric tracking system that provides feedback for control of a large gap magnetic suspension system (LGMSS).
Welch, Sharon S.↗
A Color Stereo Image Set for Evaluation of Ordnance Recognition Algorithms
This report describes a dataset of color, stereo images of ordnance collected at a live-fire test range near Nellis Air Force Base.
Algorithms Color Stereo Image Set↗
Design of source coders and joint source/channel coders for noisy channels
A theory behind a proposed joint source/channel coding approach is developed and a variable rate design approach which provides substantial improvement over current joint source/channel coder designs is obtained. The Rice algorithm as applied to the output of the Gamma Ray Detector of the Mars Orbiter is evaluated. An alternative algorithm is obtained which outperforms the Rice both in terms of data compression and noisy channel performance. A high-fidelity low-rate image compression algorithm is developed which provides almost distortionless compression of high resolution images.
Sayood, Khalid↗
Landsat Science: 40 Years of Innovation and Opportunity
Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.
Cook, Bruce D.↗
Automatic DEM Generation Using Magellan Stereo Data
The Magellan radar instrument collected a large volume of radar stereo images during its two years of operation. In order to make full use of this data an automatic means of generating digital elevation models is required. Because of Magellan's unique orbital geometry and radar image formation algorithm a number of modifications to the standard stereo processing scheme are required. This paper outlines a stereo algorithm suitable for Magellan data.
magellan radar images radar stereo images digital ↗
Algorithms and programming tools for image processing on the MPP. Appendix A: VMS command file used to implement pp command
A detailed description of the data mapping and rotation algorithms for the Massively Parallel Processor is given.
Source record↗
Compression Of Data In Imaging Radar Polarimetry
Algorithms developed to reduce number of radar polarimetric data processed to synthesize image of arbitrary combination of transmitting and receiving polarizations. Brings image-processing requirements within computing capabilities of typical users, without degrading images excessively. In scattering-matrix approach to reduction of image data, four adjacent picture elements combined into one by synthesizing new scattering matrix from scattering matrices of four elements. In phase-matrix approach, phase matrices generated from scattering matrices of four adjacent picture elements, and four phase matrices added to combine four picture elements into one.
Zebker, H. A.↗
An Automated Matching Algorithm for Magellan Stereo Data
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magellan↗
Parameterizing Spectral Surface Reflectance Relationships for the Dark Target Aerosol Algorithm Applied to A Geostationary Imager
Originally developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) in polar, sun-synchronous low-earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a Surface Reflectance Parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVISWIR). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard, the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD)retrievals from ABIE. The primary reason appears to be that geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regards to solar angles coupled with fixed view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parametrization of both red-SWIR and blue-red spectral relationships to include additional information.The revised Red-SWIR SRP includes solar zenith angle, NDVISWIR, and land-type percentage from an ancillary database. The blue-red SRP adds dependencies on the scattering angle and NDVISWIR. The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of DT AOD compared to AERONET AOD shows a reduction from 0.08 to 0.03, while the bias of local solar noon decreases from 0.12 to 0.03.The agreement between DT and AERONET AOD is established through regression slope of 1.06 and y-intercept of 0.01with correlation coefficient is0.74. By using the new SRP, the percentage of data falling within the expected error range (±0.05 + 15%) is notably risen from 54% to 78%.
Mijin Kim↗