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At least 469 records · Page 26

Short timescale stability monitoring of GOES-16 visible channels based on daily inter-calibration events with VIIRS and MODIS

The CERES project uses geostationary (GEO) imager derived broadband fluxes to estimate the diurnal flux variations between the Terra (10:30 LT) and Aqua (1:30 LT) flux obs. The GEO derived cloud properties are utilized for narrowband to broadband and angular directional model (ADM) algorithms. The GEO imager channels are first inter-calibrated to the Aqua-MODIS C6.1 calibration reference to ensure that the retrieved clouds and fluxes will be consistent. The CERES project has a 2-month latency, all GEO, MODIS and VIIRS calibration anomalies must be identified and mitigated. Convert the monthly GEO ray-matching algorithm into a daily monitoring algorithm to catch any daily calibration anomalies.

geostationary sensor calibration↗

Removing cosmic-ray hits from multiorbit HST Wide Field Camera images

We present an optimized algorithm that removes cosmic rays ('CRs') from multiorbit Hubble Space Telescope (HST) Wide Field/Planetary Camera ('WF/PC') images. It computes the image noise in every iteration from the WF/PC CCD equation. This includes all known sources of random and systematic calibration errors. We test this algorithm on WF/PC stacks of 2-12 orbits as a function of the number of available orbits and the formal Poissonian sigma-clipping level. We find that the algorithm needs greater than or equal 4 WF/PC exposures to locate the minimal sky signal (which is noticeably affected by CRs), with an optimal clipping level at 2-2.5 x sigma(sub Poisson). We analyze the CR flux detected on multiorbit 'CR stacks,' which are constructed by subtracting the best CR filtered images from the unfiltered 8-12 orbit average. We use an automated object finder to determine the surface density of CRS as a function of the apparent magnitude (or ADU flux) they would have generated in the images had they not been removed. The power law slope of the CR 'counts' (gamma approximately = 0.6 for N(m) m(exp gamma)) is steeper than that of the faint galaxy counts down to V approximately = 28 mag. The CR counts show a drop off between 28 less than or approximately V less than or approximately 30 mag (the latter is our formal 2 sigma point source sensitivity without spherical aberration). This prevents the CR sky integral from diverging, and is likely due to a real cutoff in the CR energy distribution below approximately 11 ADU per orbit. The integral CR surface density is less than or approximately 10(exp 8)/sq. deg, and their sky signal is V approximately = 25.5-27.0 mag/sq. arcsec, or 3%-13% of our NEP sky background (V = 23.3 mag/sq. arcsec), and well above the EBL integral of the deepest galaxy counts (B(sub J) approximately = 28.0 mag/sq. arcsec). We conclude that faint CRs will always contribute to the sky signal in the deepest WF/PC images. Since WFPC2 has approximately 2.7x lower read noise and a thicker CCD, this will result in more CR detections than in WF/PC, potentially affecting approximately 10%-20% of the pixels in multiorbit WFPC2 data cubes.

Windhorst, Rogier A.↗

Tracking ocean wave spectrum from SAR images

An end to end algorithm for recovery of ocean wave spectral peaks from Synthetic Aperture Radar (SAR) images is described. Current approaches allow precisions of 1 percent in wave number, and 0.6 deg in direction.

Goldfinger, A. D.↗

Investigation of image enhancement techniques for the development of a self-contained airborne radar navigation system

This study was devoted to an investigation of the feasibility of applying advanced image processing techniques to enhance radar image characteristics that are pertinent to the pilot's navigation and guidance task. Millimeter (95 GHz) wave radar images for the overwater (i.e., offshore oil rigs) and overland (Heliport) scenario were used as a data base. The purpose of the study was to determine the applicability of image enhancement and scene analysis algorithms to detect and improve target characteristics (i.e., manmade objects such as buildings, parking lots, cars, roads, helicopters, towers, landing pads, etc.) that would be helpful to the pilot in determining his own position/orientation with respect to the outside world and assist him in the navigation task. Results of this study show that significant improvements in the raw radar image may be obtained using two dimensional image processing algorithms. In the overwater case, it is possible to remove the ocean clutter by thresholding the image data, and furthermore to extract the target boundary as well as the tower and catwalk locations using noise cleaning (e.g., median filter) and edge detection (e.g., Sobel operator) algorithms.

Phatak, A. V.↗

Near real-time stereo vision system

The apparatus for a near real-time stereo vision system for use with a robotic vehicle is described. The system is comprised of two cameras mounted on three-axis rotation platforms, image-processing boards, a CPU, and specialized stereo vision algorithms. Bandpass-filtered image pyramids are computed, stereo matching is performed by least-squares correlation, and confidence ranges are estimated by means of Bayes' theorem. In particular, Laplacian image pyramids are built and disparity maps are produced from the 60 x 64 level of the pyramids at rates of up to 2 seconds per image pair. The first autonomous cross-country robotic traverses (of up to 100 meters) have been achieved using the stereo vision system of the present invention with all computing done onboard the vehicle. The overall approach disclosed herein provides a unifying paradigm for practical domain-independent stereo ranging.

Anderson, Charles H.↗

Neural networks: Application to medical imaging

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Clarke, Laurence P.↗

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.

Source record↗

Hybrid-dual-fourier tomographic algorithm for a fast three-dimensionial optical image reconstruction in turbid media

A reconstruction technique for reducing computation burden in the 3D image processes, wherein the reconstruction procedure comprises an inverse and a forward model. The inverse model uses a hybrid dual Fourier algorithm that combines a 2D Fourier inversion with a 1D matrix inversion to thereby provide high-speed inverse computations. The inverse algorithm uses a hybrid transfer to provide fast Fourier inversion for data of multiple sources and multiple detectors. The forward model is based on an analytical cumulant solution of a radiative transfer equation. The accurate analytical form of the solution to the radiative transfer equation provides an efficient formalism for fast computation of the forward model.

Alfano, Robert R.↗

Digital processing considerations for extraction of ocean wave image spectra from raw synthetic aperture radar data

The digital processing requirements of several algorithms for extracting the spectrum of a detected synthetic aperture radar (SAR) image from the raw SAR data are described and compared. The most efficient algorithms for image spectrum extraction from raw SAR data appear to be those containing an intermediate image formation step. It is shown that a recently developed compact formulation of the image spectrum in terms of the raw data is computationally inefficient when evaluated directly, in comparison with the classical method where matched-filter image formation is an intermediate result. It is also shown that a proposed indirect procedure for digitally implementing the same compact formulation is somewhat more efficient than the classical matched-filtering approach. However, this indirect procedure includes the image formation process as part of the total algorithm. Indeed, the computational savings afforded by the indirect implementation are identical to those obtained in SAR image formation processing when the matched-filtering algorithm is replaced by the well-known 'dechirp-Fourier transform' technique. Furthermore, corrections to account for slant-to-ground range conversion, spherical earth, etc., are often best implemented in the image domain, making intermediate image formation a valuable processing feature.

Lahaie, I. J.↗

Improvements in Speed and Functionality of a 670-GHz Imaging Radar

Significant improvements have been made in the instrument originally described in a prior NASA Tech Briefs article: Improved Speed and Functionality of a 580-GHz Imaging Radar (NPO-45156), Vol. 34, No. 7 (July 2010), p. 51. First, the wideband YIG oscillator has been replaced with a JPL-designed and built phase-locked, low-noise chirp source. Second, further refinements to the data acquisition and signal processing software have been performed by moving critical code sections to C code, and compiling those sections to Windows DLLs, which are then invoked from the main LabVIEW executive. This system is an active, single-pixel scanned imager operating at 670 GHz. The actual chirp signals for the RF and LO chains were generated by a pair of MITEQ 2.5 3.3 GHz chirp sources. Agilent benchtop synthesizers operating at fixed frequencies around 13 GHz were then used to up-convert the chirp sources to 15.5 16.3 GHz. The resulting signals were then multiplied 36 times by a combination of off-the-shelf millimeter- wave components, and JPL-built 200- GHz doublers and 300- and 600-GHz triplers. The power required to drive the submillimeter-wave multipliers was provided by JPL-built W-band amplifiers. The receive and transmit signal paths were combined using a thin, high-resistivity silicon wafer as a beam splitter. While the results at present are encouraging, the system still lacks sufficient speed to be usable for practical applications in a contraband detection. Ideally, an image acquisition speed of ten seconds, or a factor of 30 improvement, is desired. However, the system improvements to date have resulted in a factor of five increase in signal acquisition speed, as well as enhanced signal processing algorithms, permitting clearer imaging of contraband objects hidden underneath clothing. In particular, advances in three distinct areas have enabled these performance enhancements: base source phase noise reduction, chirp rate, and signal processing. Additionally, a second pixel was added, automatically reducing the imaging time by a factor of two. Although adding a second pixel to the system doubles the amount of submillimeter components required, some savings in microwave hardware can be realized by using a common low-noise source.

Dengler, Robert J.↗

Context distribution estimation for contextual classification of multispectral image data

A classification algorithm incorporating contextual information in a general, statistical manner is presented. Methods are investigated for obtaining adequate estimates of the context distribution (a statistical characterization of context) upon which the classification algorithm depends. Finally, a method of estimating optimal algorithm parameters prior to performing preliminary classifications is explored.

Tilton, J. C.↗

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

Chang, L. Aron↗

Development of a stereo analysis algorithm for generating topographic maps using interactive techniques of the MPP

A local area matching algorithm was developed on the Massively Parallel Processor (MPP). It is an iterative technique that first matches coarse or low resolution areas and at each iteration performs matches of higher resolution. Results so far show that when good matches are possible in the two images, the MPP algorithm matches corresponding areas as well as a human observer. To aid in developing this algorithm, a control or shell program was developed for the MPP that allows interactive experimentation with various parameters and procedures to be used in the matching process. (This would not be possible without the high speed of the MPP). With the system, optimal techniques can be developed for different types of matching problems.

Strong, James P.↗

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗