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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Java Image I/O for VICAR, PDS, and ISIS

This library, written in Java, supports input and output of images and metadata (labels) in the VICAR, PDS image, and ISIS-2 and ISIS-3 file formats. Three levels of access exist. The first level comprises the low-level, direct access to the file. This allows an application to read and write specific image tiles, lines, or pixels and to manipulate the label data directly. This layer is analogous to the C-language "VICAR Run-Time Library" (RTL), which is the image I/O library for the (C/C++/Fortran) VICAR image processing system from JPL MIPL (Multimission Image Processing Lab). This low-level library can also be used to read and write labeled, uncompressed images stored in formats similar to VICAR, such as ISIS-2 and -3, and a subset of PDS (image format). The second level of access involves two codecs based on Java Advanced Imaging (JAI) to provide access to VICAR and PDS images in a file-format-independent manner. JAI is supplied by Sun Microsystems as an extension to desktop Java, and has a number of codecs for formats such as GIF, TIFF, JPEG, etc. Although Sun has deprecated the codec mechanism (replaced by IIO), it is still used in many places. The VICAR and PDS codecs allow any program written using the JAI codec spec to use VICAR or PDS images automatically, with no specific knowledge of the VICAR or PDS formats. Support for metadata (labels) is included, but is format-dependent. The PDS codec, when processing PDS images with an embedded VIAR label ("dual-labeled images," such as used for MER), presents the VICAR label in a new way that is compatible with the VICAR codec. The third level of access involves VICAR, PDS, and ISIS Image I/O plugins. The Java core includes an "Image I/O" (IIO) package that is similar in concept to the JAI codec, but is newer and more capable. Applications written to the IIO specification can use any image format for which a plug-in exists, with no specific knowledge of the format itself.

Deen, Robert G.↗
NASA NTRS1993

Robust algebraic image enhancement for intelligent control systems

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Lerner, Bao-Ting↗
DOE OSTI2016

Distributed Halide

Many image processing tasks are naturally expressed as a pipeline of small computational kernels known as stencils. Halide is a popular domain-specific language and compiler designed to implement image processing algorithms. Halide uses simple language constructs to express what to compute and a separate scheduling co-language for expressing when and where to perform the computation. This approach has demonstrated performance comparable to or better than hand-optimized code. Until now, however, Halide has been restricted to parallel shared memory execution, limiting its performance for memory-bandwidth-bound pipelines or large-scale image processing tasks. We present an extension to Halide to support distributed-memory parallel execution of complex stencil pipelines. These extensions compose with the existing scheduling constructs in Halide, allowing expression of complex computation and communication strategies. Existing Halide applications can be distributed with minimal changes, allowing programmers to explore the tradeoff between recomputation and communication with little effort. Approximately 10 new of lines code are needed even for a 200 line, 99 stage application. On nine image processing benchmarks, our extensions give up to a 1.4× speedup on a single node over regular multithreaded execution with the same number of cores, by mitigating the effects of non-uniform memory access. The distributed benchmarks achieve up to 18× speedup on a 16 node testing machine and up to 57× speedup on 64 nodes of the NERSC Cori supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Detecting the Extent of Cellular Decomposition after Sub-Eutectoid Annealing in Rolled UMo Foils

This report presents an automated image processing approach to quantifying microstructure image data, specifically the extent of eutectoid (cellular) decomposition in rolled U-10Mo foils. An image processing approach is used here to be able to quantitatively describe microstructure image data in order to relate microstructure to processing parameters (time, temperature, deformation).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

Characterization of Axial Inducer Cavitation Instabilities via High Speed Video Recordings

Sub-scale water tests were undertaken to assess the viability of utilizing high resolution, high frame-rate digital video recordings of a liquid rocket engine turbopump axial inducer to characterize cavitation instabilities. These high speed video (HSV) images of various cavitation phenomena, including higher order cavitation, rotating cavitation, alternating blade cavitation, and asymmetric cavitation, as well as non-cavitating flows for comparison, were recorded from various orientations through an acrylic tunnel using one and two cameras at digital recording rates ranging from 6,000 to 15,700 frames per second. The physical characteristics of these cavitation forms, including the mechanisms that define the cavitation frequency, were identified. Additionally, these images showed how the cavitation forms changed and transitioned from one type (tip vortex) to another (sheet cavitation) as the inducer boundary conditions (inlet pressures) were changed. Image processing techniques were developed which tracked the formation and collapse of cavitating fluid in a specified target area, both in the temporal and frequency domains, in order to characterize the cavitation instability frequency. The accuracy of the analysis techniques was found to be very dependent on target size for higher order cavitation, but much less so for the other phenomena. Tunnel-mounted piezoelectric, dynamic pressure transducers were present throughout these tests and were used as references in correlating the results obtained by image processing. Results showed good agreement between image processing and dynamic pressure spectral data. The test set-up, test program, and test results including H-Q and suction performance, dynamic environment and cavitation characterization, and image processing techniques and results will be discussed.

Arellano, Patrick↗
NASA NTRS2007

A Software Platform for Post-Processing Waveform-Based NDE

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

Roth, Donald J.↗
DOE OSTI2016

MO-B-207B-00: Harmonization & Robustness in Radiomics

Feature extraction for radiomics studies typically comprises the following stages: Imaging, segmentation, image processing, and feature extraction. Each of these stages has associated uncertainties that can affect the quality of a radiomics model created using the resulting image features. For example, the imaging device manufacturer and model have been shown to impact the values of image features, as have pixel size and imaging protocol parameters. Image processing, such as low-pass filtering to reduce noise, also changes calculated image features and should be designed to optimize the information content of the resulting features. The details of certain feature algorithms, such as co-occurrence matrix bin sizes, are also important, and should be optimized for specific radiomics tasks. The volume of the region of interest should be considered as image features can be related to volume and can give unanticipated results when the volumes are too small. In this session we will describe approaches to quantify the variabilities in radiomics studies, including the most recent results quantifying these variabilities for CT, MRI and PET imaging. We will discuss methods to optimize image processing and feature extraction in order to maximize the information content of the image features. Finally, we will describe work to harmonize imaging protocols and feature calculations to help minimize uncertainties in radiomics studies. Learning Objectives: At the end of this session, participants will be able to: Identify the sources of uncertainty in radiomics studies (CT, PET, and MRI imaging) Describe methods for quantifying the magnitude of uncertainties Describe approaches for mitigating the effects of the uncertainties on radiomics models Funding from NIH, CPRIT, Varian, Elekta; L. Court, NCI, CPRIT, Varian, Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-B-207B-01: Harmonization & Robustness in Radiomics

Feature extraction for radiomics studies typically comprises the following stages: Imaging, segmentation, image processing, and feature extraction. Each of these stages has associated uncertainties that can affect the quality of a radiomics model created using the resulting image features. For example, the imaging device manufacturer and model have been shown to impact the values of image features, as have pixel size and imaging protocol parameters. Image processing, such as low-pass filtering to reduce noise, also changes calculated image features and should be designed to optimize the information content of the resulting features. The details of certain feature algorithms, such as co-occurrence matrix bin sizes, are also important, and should be optimized for specific radiomics tasks. The volume of the region of interest should be considered as image features can be related to volume and can give unanticipated results when the volumes are too small. In this session we will describe approaches to quantify the variabilities in radiomics studies, including the most recent results quantifying these variabilities for CT, MRI and PET imaging. We will discuss methods to optimize image processing and feature extraction in order to maximize the information content of the image features. Finally, we will describe work to harmonize imaging protocols and feature calculations to help minimize uncertainties in radiomics studies. Learning Objectives: At the end of this session, participants will be able to: Identify the sources of uncertainty in radiomics studies (CT, PET, and MRI imaging) Describe methods for quantifying the magnitude of uncertainties Describe approaches for mitigating the effects of the uncertainties on radiomics models Funding from NIH, CPRIT, Varian, Elekta; L. Court, NCI, CPRIT, Varian, Elekta.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1999

Modeling of polychromatic attenuation using computed tomography reconstructed images

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

NASA Discipline Musculoskeletal↗
NASA NTRS1983

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.↗
DOE OSTI2020

Mapping of Benthic Habitats at Marine Renewable Energy Sites Using Multibeam Echosounder and Sediment Profile Imaging Technologies

Objectives/Scope: The goal of this work was to develop a consistent and semi-automated seafloor survey method for generating high-resolution, benthic habitat maps for environmental assessments and monitoring of marine renewable energy sites. Sediment profile and plan view imaging (SPI/PV) technology was combined with multibeam bathymetry and acoustic backscatter methods to demonstrate a rapid, cost-effective benthic mapping protocol. A key technical innovation of this project was the development of an image processing platform that automatically measures key features from the images. Methods: Multibeam echosounder (MBES) acoustic and SPI/PV surveys were conducted at three coastal areas off the U.S. west coast, including the PacWave South energy test site off of Newport, Oregon. Point data on physical and biological sediment conditions obtained from the SPI/PV imagery were used to efficiently ground-truth the high-resolution MBES bathymetry and backscatter mosaics. The SPI camera is an optical corer that obtains an undisturbed 21 by 15 cm, high-resolution, cross-sectional image of the sediment–water interface and upper sediment column. The plan view camera attached to the SPI camera frame captures a downward looking view of the seabed immediately before the SPI image is obtained. As part of this project, we developed a computer vision image processing platform (iSPI) that uses deep convolutional neural networks and other approaches to automatically identify and measure key features in the images, such as grain size and surface relief. Results: Detailed benthic habitat maps were generated using this mapping approach for three different marine settings. The sites mapped included a silt-dominated embayment; a sloping, nearshore, transitional very fine to coarse sand bottom; and a medium, sand-dominated continental shelf marine energy test site. In each case, acoustic and imaging surveys were completed in less than week, and detailed benthic habitat maps were generated within 60 days. The results were placed within the Coastal and Marine Ecological Classification Standard (CMECS) habitat mapping framework, and various combinations of the bathymetry, backscatter, and SPI and PV data were used to generate CMECS component maps. Novel Information: This project developed and demonstrated a repeatable and cost-effective approach for efficiently mapping benthic habitat conditions over broad areas of the seafloor by combining state-of-the-art acoustic and imaging techniques. The primary survey tools used in this project have been used previously in both the offshore renewable (wind) and oil and gas sectors to map and monitor benthic environments. This project’s innovations include 1) the focused use of high-resolution SPI/PV imagery to ground-truth acoustic mosaics, and 2) the development of a computer automated image analysis processing tool that both streamlines and standardizes the generation of data from the imagery and makes the data extraction process more cost-effective and repeatable.

13 HYDRO ENERGY↗
DOE OSTI2022

Automated Calculation of U-10Mo Fuel and Zr Cladding Thickness

Hand calculation and verification of cladding and fuel thickness in a hot-isostatically pressed uranium-molybdenum (U-10Mo) alloy can incur human errors and longer image processing time when analyzing a large set of cross-sectional images. To help alleviate both time cost and errors made in hand measurements, an automated image processing procedure was developed using Octave, an open-source MATLAB alternative, to repeatedly determine the thickness of Zr and U-10Mo layers. U-10Mo specimens were imaged using standard secondary electron and backscattered-electron imaging at 250× magnification to capture the various layers present in U-10Mo. Further image processing used pixel-by-pixel calculation of the Zr and U-10Mo layers to gather quantitative statistics on the thickness variations associated with each of the layers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1984

Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico

A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area

Rebillard, PH.↗
NASA NTRS1987

Real-time model-based vision system for object acquisition and tracking

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Wilcox, Brian↗
NASA NTRS1990

A mixture neural net for multispectral imaging spectrometer processing

Each spatial region viewed by an imaging spectrometer contains various elements in a mixture. The elements present and the amount of each are to be determined. A neural net solution is considered. Initial optical neural net hardware is described. The first simulations on the component requirements of a neural net are considered. The pseudoinverse solution is shown to not suffice, i.e. a neural net solution is required.

Casasent, David↗