Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “IMAGE PROCESSING”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

WE-G-207-04: Non-Local Total-Variation (NLTV) Combined with Reweighted L1-Norm for Compressed Sensing Based CT Reconstruction

Purpose: Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total-variation (TV) in L1-minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non-local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1-norm into it for more precise reconstruction. Methods: TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes more global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1-min., designed for approximation to ideal L0-min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1-min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV. Results: In both cases, conventional and reweighted NLTV outperform TV min. in signal-to-noise ratio (SNR) and root-mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1-norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process. Conclusion: NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1-norm, while maintaining greater robustness to the noise effect than TV min.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Defect Detection of Industrial Radiography Images of Ammonia Pipes by a Sparse Coding Model

Pipeline transportation systems for liquid anhydrous ammonia require periodic inspections for pipe defects. Defects such as crack-like flaws, including those due to stress corrosion and fatigue crack growth and fatigue of welded joints, can be tested by in situ radiography testing (RT). It is required that the detection technique should reveal the defect region without any significant distortion. Imaging noise such as that due to radiation scattering reduces contrast over the whole or part of the image, causing a reduction in image quality. Various image processing methods can be utilized to improve the outcome of RT of pipes. The sparse coding model is a powerful contrast improvement algorithm, but it tends to eliminate imaging details, passing them off as noise. We present a novel implementation of the sparse coding model based on a probabilistic interpretation to improve defect detection in ammonia pipelines radiography images. The performance of this procedure was evaluated in radiographic images of defect and corrosion regions for different pipe types. For ammonia pipes, the technique was found to offer a significant improvement in defect detection while preserving imaging details.

42 ENGINEERING↗
NASA NTRS1984

Improved Gamma-and X-Ray Pinhole Camera

Electronic additions increase image quality. Digital image-processing equipment electronically performs functions of S1 and D2 improving resolution and adding capability for image storage and further processing. System useful in nuclear medicine or radioisotope imaging, tomography and nuclear industry.

Yin, L. I.↗
DOE OSTI2020

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗
DOE OSTI2018

Annatto-colored Poly(3-hydroxybutyrate): A Comprehensive Study on Photodegradation

Annatto natural colorant was extracted from annatto seeds (Bixa Orellana L.) by using ultrasound. Structural characterization of the extract was done by FTIR. The aim of the present work was the developement and characterization of biodegradable colored films based on poly(3-hydroxybutyrate) by using annatto colorant. The annatto content in the films was varied from 0.2 to 3.0% (w/w). The lightfastness of colored films when exposed to UVA radiation was controlled by using RGB color system. In color image processing, a pixel is often defined by three values corresponding to the tristimuli R (Red), G (Green) and B (Blue). With the addition of the annatto colorant, photodegradation of films under UVA exposure seemed to be improved. The good thermal stability of the colored film with 3.0% (w/w) of annatto colorant was confirmed by thermogravimetric analysis. Surface morphology of the colored film with 3.0% (w/w) of annatto colorant was examined by SEM prior and after 240 h of UVA exposure. The SEM micrographs suggested that annatto colorant has acted as hiding agent, reducing the photodegradation processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

PERSISTENCE MAPPING USING EUV SOLAR IMAGER DATA

We describe a simple image processing technique that is useful for the visualization and depiction of gradually evolving or intermittent structures in solar physics extreme-ultraviolet imagery. The technique is an application of image segmentation, which we call “Persistence Mapping,” to isolate extreme values in a data set, and is particularly useful for the problem of capturing phenomena that are evolving in both space and time. While integration or “time-lapse” imaging uses the full sample (of size N ), Persistence Mapping rejects ( N − 1)/ N of the data set and identifies the most relevant 1/ N values using the following rule: if a pixel reaches an extreme value, it retains that value until that value is exceeded. The simplest examples isolate minima and maxima, but any quantile or statistic can be used. This paper demonstrates how the technique has been used to extract the dynamics in long-term evolution of comet tails, erupting material, and EUV dimming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

Two and Three Dimensional near Infrared Subcutaneous Structure Imager Using Real Time Nonlinear Video Processing

An imager is provided for viewing subcutaneous structures. In an embodiment of the invention, the imager includes a camera configured to generate a video frame, and an adaptive nonlinear processor. The adaptive nonlinear processor is configured to adjust a signal of the video frame below a first threshold to a maximum dark level and to adjust the signal of the video frame above a second threshold to a maximum light level. The imager further includes a display, configured to display the processed video frame.

Krasowski, Michael J↗
DOE OSTI2024

Skipper-in-CMOS: Nondestructive Readout With Subelectron Noise Performance for Pixel Detectors

The Skipper-in-CMOS image sensor integrates the nondestructive readout capability of skipper charge coupled devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode (PPD) in a CMOS imaging process while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly parallel processing. The first results obtained from a ${15} \times {15}~\mu $ m2 pixel cell of a Skipper-in-CMOS sensor fabricated in Tower Semiconductor’s commercial 180-nm CMOS image sensor process are presented. Measurements confirm the expected reduction of the readout noise with the number of samples down to deep subelectron noise of $0.15\text {e}^ - $ , demonstrating the charge transfer operation from the PPD and the single photon counting operation when the sensor is exposed to light. This article also discusses new testing strategies employed for its operation and characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Progress Update on Iterative Reconstruction of Neutron Tomographic Images

This report satisfies the fiscal year 2016 technical deliverable to report on progress in development of fast iterative reconstruction algorithms for project OR16-3DTomography-PD2Jb, "3D Tomography and Image Processing Using Fast Neutrons." This project has two overall goals. The first of these goals is to extend associated-particle fast neutron transmission and, particularly, induced-reaction tomographic imaging algorithms to three dimensions. The second of these goals is to automatically segment the resultant tomographic images into constituent parts, and then extract information about the parts, such as the class of shape and potentially shape parameters. This report addresses of the component of the project concerned with three-dimensional (3D) image reconstruction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2001

Machine vision guided sensor positioning system for leaf temperature assessment

A sensor positioning system was developed for monitoring plants' well-being using a non-contact sensor. Image processing algorithms were developed to identify a target region on a plant leaf. A novel algorithm to recover view depth was developed by using a camera equipped with a computer-controlled zoom lens. The methodology has improved depth recovery resolution over a conventional monocular imaging technique. An algorithm was also developed to find a maximum enclosed circle on a leaf surface so the conical field-of-view of an infrared temperature sensor could be filled by the target without peripheral noise. The center of the enclosed circle and the estimated depth were used to define the sensor 3-D location for accurate plant temperature measurement.

NASA Discipline Life Support Systems↗
NASA NTRS1989

Measuring Airflow With Digital Holographic Interferometry

Digital image-processing system assists in analysis of holographic interferometric images of flow about airfoil. Operating semiautomatically, identifies, counts, and labels interference fringes, then processes distances between fringes into distribution of pressure on surface of airfoil. Yields data on pressure faster than manual image-analyses techniques, and data compares favorably with those obtained by manual analysis and by probe measurements of pressure. Uses computer programs evaluating interferograms along straight or curved lines represented by polygon segments. User prompted for such inputs as reference points and fringe number. Digitizes holographic interferograms of flow and processes them into data of pressure or other properties of flow.

Torres, Francisco J.↗
DOE OSTI2018

Characteristics of a New X-Ray Imaging System for Interventional Procedures: Improved Image Quality and Reduced Radiation Dose

PurposeTo compare image quality and radiation exposure between a new angiographic imaging system and the preceding generation system during uterine artery embolization (UAE).Materials and MethodsIn this retrospective, IRB-approved two-arm study, 54 patients with symptomatic uterine fibroids were treated with UAE on two different angiographic imaging systems. The new system includes optimized acquisition parameters and real-time image processing algorithms. Air kerma (AK), dose area product (DAP) and acquisition time for digital fluoroscopy (DF) and digital subtraction angiography (DSA) were recorded. Body mass index was noted as well. DF image quality was assessed objectively by image noise measurements. DSA image quality was rated by two blinded, independent readers on a four-rank scale. Statistical differences were assessed with unpaired t tests and Wilcoxon rank-sum tests.ResultsThere was no significant difference between the patients treated on the new (n = 36) and the old system (n = 18) regarding age (p = 0.10), BMI (p = 0.18), DF time (p = 0.35) and DSA time (p = 0.17). The new system significantly reduced the cumulative AK and DAP by 64 and 72%, respectively (median 0.58 Gy and 145.9 Gy*cm{sup 2} vs. 1.62 Gy and 526.8 Gy*cm{sup 2}, p < 0.01 for both). Specifically, DAP for DF and DSA decreased by 59% (75.3 vs. 181.9 Gy*cm{sup 2}, p < 0.01) and 78% (67.6 vs. 312.2 Gy*cm{sup 2}, p < 0.01), respectively. The new system achieved a significant decrease in DF image noise (p < 0.01) and a significantly better DSA image quality (p < 0.01).ConclusionsThe new angiographic imaging system significantly improved image quality and reduced radiation exposure during UAE procedures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Generalized Quantum Convolution for Multidimensional Data

The convolution operation plays a vital role in a wide range of critical algorithms across various domains, such as digital image processing, convolutional neural networks, and quantum machine learning. In existing implementations, particularly in quantum neural networks, convolution operations are usually approximated by the application of filters with data strides that are equal to the filter window sizes. One challenge with these implementations is preserving the spatial and temporal localities of the input features, specifically for data with higher dimensions. In addition, the deep circuits required to perform quantum convolution with a unity stride, especially for multidimensional data, increase the risk of violating decoherence constraints. In this work, we propose depth-optimized circuits for performing generalized multidimensional quantum convolution operations with unity stride targeting applications that process data with high dimensions, such as hyperspectral imagery and remote sensing. We experimentally evaluate and demonstrate the applicability of the proposed techniques by using real-world, high-resolution, multidimensional image data on a state-of-the-art quantum simulator from IBM Quantum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1972

Review of coherent optical data processing

The fundamental features of coherent optical data processing systems are reviewed for potential application to image processing. The application of optical spatial filtering to image mapping and cloud motion is discussed.

Vanderlugt, A.↗
NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗
DOE OSTI2016

SU-F-T-114: A Novel Anatomically Predictive Extension Model of Computational Human Phantoms for Dose Reconstruction in Retrospective Epidemiological Studies of Second Cancer Risks in Radiotherapy Patients

Purpose: Recent advances in cancer treatments have greatly increased the likelihood of post-treatment patient survival. Secondary malignancies, however, have become a growing concern. Epidemiological studies determining secondary effects in radiotherapy patients require assessment of organ-specific dose both inside and outside the treatment field. An essential input for Monte Carlo modeling of particle transport is radiological images showing full patient anatomy. However, in retrospective studies it is typical to only have partial anatomy from CT scans used during treatment planning. In this study, we developed a multi-step method to extend such limited patient anatomy to full body anatomy for estimating dose to normal tissues located outside the CT scan coverage. Methods: The first step identified a phantom from a library of body size-dependent computational human phantoms by matching the height and weight of patients. Second, a Python algorithm matched the patient CT coverage location in relation to the whole body phantom. Third, an algorithm cut the whole body phantom and scaled them to match the size of the patient. Then, merged the two anatomies into one whole body. We entitled this new approach, Anatomically Predictive Extension (APE). Results: The APE method was examined by comparing the original chest-abdomen-pelvis CT images of the five patients with the APE phantoms developed from only the chest part of the CAP images and whole body phantoms. We achieved average percent differences of tissue volumes of 25.7%, 34.2%, 16.5%, 26.8%, and 31.6% with an average of 27% across all patients. Conclusion: Our APE method extends the limited CT patient anatomy to whole body anatomy by using image processing and computational human phantoms. Our ongoing work includes evaluating the accuracy of these APE phantoms by comparing normal tissue doses in the APE phantoms and doses calculated for the original full CAP images under generic radiotherapy simulations. This research was supported by the NIH Intramural Research Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The formation of quantum images and their transformation and super-resolution reading

Images formed by light with suppressed photon fluctuations are interesting objects for studies with the aim of increasing their limiting information capacity and quality. This light in the sub-Poisson state can be prepared in a resonator filled with a medium with Kerr nonlinearity, in which self-phase modulation takes place. Spatially and temporally multimode light beams are studied and the production of spatial frequency spectra of suppressed photon fluctuations is described. The efficient operation regimes of the system are found. A particular schematic solution is described, which allows one to realize the potential possibilities laid in the formation of the squeezed states of light to a maximum degree during self-phase modulation in a resonator for the maximal suppression of amplitude quantum noises upon two-dimensional imaging. The efficiency of using light with suppressed quantum fluctuations for computer image processing is studied. An algorithm is described for interpreting measurements for increasing the resolution with respect to the geometrical resolution. A mathematical model that characterizes the measurement scheme is constructed and the problem of the image reconstruction is solved. The algorithm for the interpretation of images is verified. Conditions are found for the efficient application of sub-Poisson light for super-resolution imaging. It is found that the image should have a low contrast and be maximally transparent.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗