An image navigation (NAV) and registration (INR) performance assessment tool set (IPATS) was developed to assess the US Geostationary Operational Environmental Satellite R-series (GOES-R) Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance. IPATS produces five INR metrics for level 1B ABI images: navigation, channel-to-channel registration, frame-to-frame registration, swath-to-swath registration, and within-frame registration. IPATS also produces one INR metric for GLM: navigation of background images. The high-precision INR metrics produced by IPATS are critical to INR performance evaluation and long-term monitoring. IPATS INR metrics also provide feedback to INR engineers for tuning the navigation algorithms and parameters to further refine INR performance. IPATS utilizes a modular algorithm design to allow the user-selectable data processing sequence and configuration parameters. We first describe the algorithmic design and the implementation of IPATS. Next, it describes the investigation of the optimization of the configuration parameters to reduce measurement errors. Finally, sample INR performance is presented, including GOES-16 and GOES-17 ABI NAV performance from postlaunch test to November 2019 and the comparison of example 24-h INR performance against the mission performance requirements. The INR assessment results show that both GOES-R ABIs are in compliance with the mission INR requirements.
In developing software for independent verification and validation (IV and V) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite – R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.
In this paper we model sub-pixel image registration for a generic earth-observing satellite system with a focal plane using two offset time delay and integrate (TDI) arrays in the focal plane to improve the achievable ground resolution over the resolution achievable with a single array. The modeling process starts with a high-resolution image as ground truth. The Parameterized Image Chain Analysis & Simulation Software (PICASSO) modeling tool is used to degrade the images to match the optical transfer function, sampling, and noise characteristics of the target system. The model outputs a pair of images with a separation close to the nominal half-pixel separation between the overlapped arrays. A registration estimation algorithm is used to measure the offset for image reconstruction. The two images are aligned and summed on a grid with twice the capture resolution. We compare the resolution in images between the inputs before overlap, the reconstructed image, and a simulation for the image which would have been captured on a focal plane with twice the resolution. We find the performance to always be better than the lower resolution baseline, and to approach the performance of the high-resolution array in the ideal case. We show that the overlapped array imager significantly outperforms both the conventional high- and low-resolution imagers in conditions with high image smear.
The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of image quality from fundamental design parameters - is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.
The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image
quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of
image quality from fundamental design parameters - is an important part of this design process. At The Aerospace
Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain
Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how,
starting with a high quality input image and hypothetical design descriptions representative of the current state of the art
in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision
processes of designers and program managers alike.
In this paper we model sub-pixel image registration for a generic earth-observing satellite system with a focal plane
using two offset Time Delay and Integrate (TDI) arrays in the focal plane to improve the achievable ground resolution
over the resolution achievable with a single array. The modeling process starts with a high-resolution image as ground
truth. The Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) modeling tool is used to degrade
the images to match the optical transfer function, sampling, and noise characteristics of the target system. The model
outputs a pair of images with a separation close to the nominal half-pixel separation between the overlapped arrays. A
registration estimation algorithm is used to measure the offset for image reconstruction. The two images are aligned and
summed on a grid with twice the capture resolution. We compare the resolution in images between the inputs before
overlap, the reconstructed image, and a simulation for the image which would have been captured on a focal plane with
twice the resolution. We find the performance to always be better than the lower resolution baseline, and to approach
the performance of the high-resolution array in the ideal case. We show that the overlapped array imager significantly
outperforms both the conventional high- and low-resolution imagers in conditions with high image smear.
When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images,
interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the
sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output
measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the
outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and
optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than
0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error
for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest
measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by
modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.
Accurate registration of image pairs is critical to a number of image processing tasks, including image splicing, change
detection, image co-addition, and super-resolution processing. We have applied digital Fourier plane correlation and
optical joint-transform correlation to image registration. We demonstrated RMS registration accuracy of 0.09 pixels for
a digital system and 0.1 pixels for an optical system. The experimental system uses an electrically addressed spatial
light modulator (SLM) at the input plane of a joint transform correlator and an optically addressed SLM at the Fourier
plane. We operate our optical system in burst mode at the rate of 50 correlations per second. The paper describes digital
and experimental implementations of the image registration system. We discuss preprocessing algorithms used to
prepare inputs for correlation, post-processing algorithms to interpolate the output, and the effect of these processing
variations on system performance.
The binary joint transform correlator (BJTC) can provide sub-pixel correlation location accuracy for a pair of almost identical inputs, as is the case when computing the registration offset between two overlapping images from the same sensor. Applications include noise cancellation, motion compensation, super-resolution processing, and image splicing. We experimentally demonstrated sub-pixel registration and image co-addition. Our results show a resolution improves by a factor of almost two compared to normal integration. This paper details early results in an ongoing project.
A 1D IR lock-in focal plane array (FPA) for extremely weak signal imaging has been demonstrated. The experimental system consists of an object with modulated image signal, a high speed InGaAs linear photodetector array as receiver, a CMOS lock-in linear array read-out circuit, and a focal plane array test system. The system can detect extremely weak signals immersed in strong background. Preliminary test shows that under room temperature each of the pixels in the 1D lock-in FPA can read out modulated signal 5 orders smaller than the background. The InGaAs detector array response is
from 0.8 μm to 1.6 μm (peak at 1.2 μm). The lock-in array read-out circuit uses a correlated multi-cycle integrator, which can operate in several modes such as gated integration, and phase-sensitive integration with background subtraction. The 1D lock-in FPA works as a pixel to pixel lock-in amplifier, wherein very small signals may be extracted from a much strong background if the frequency of the illuminating source (usually IR light sources) is known. Simulation results are also reported. Experimental results based on an IR illuminating source are demonstrated.
In November 2003, a Space Environmental Effects Working Group meeting in El Segundo, CA developed technology roadmaps and recommended Government investment strategies for key technologies needed for large space imaging systems. This paper summarizes results from the session on focal plane array (FPA) technology. The FPA session
recommended continued emphasis and additional investments to strengthen the manufacturing infrastructure for production and test of advanced focal planes and readouts, especially those operating at cryogenic temperatures and in radiation environments.
The Defense Threat Reduction Agency (DTRA) and National Aeronautics and Space Administration (NASA) Goddard Space Flight Center are collaborating to develop the Carrier Plus sensor experiment platform as a capability of the Space Environment Testbed (SET). The Space Environment Testbed (SET) provides flight opportunities for technology
experiments as part of NASA's Living With a Star (LWS) program. The Carrier Plus will provide new capability to characterize sensor technologies such as state-of-the-art visible focal plane arrays (FPAs) in a natural space radiation environment. The technical objectives include on-orbit validation of recently developed FPA technologies and sensor performance prediction methodologies, as well as characterization of the FPA radiation response to total ionizing dose damage, displacement damage and transients. It is expected that the sensor experiment will carry 4-6 FPAs and associated radiation correlative environment monitors (CEMs) for a 2008 launch. Sensor technology candidates may include n- and p-charge coupled devices (CCDs), active pixel sensors (APS), and hybrid CMOS arrays. This paper will describe the Carrier Plus goals and objectives, as well as provide details about the architecture and design. More information on the LWS program can be found at http://lws.gsfc.nasa.gov/
gov/. Business announcements for LWS/SET and program briefings are posted at http://lws-set.gsfc.nasa.gov.
This study demonstrates that the single-lens joint transform correlator is capable of position resolution accuracy on the order of a half micron. The single-lens joint transform correlator (JTC) is an extension of the chirp-encoded JTC in which the output lens has been eliminated. This is done by realizing that a Fresnel zone plate is formed in the joint power spectrum of the chirp-encoded JTC. This zone plate is illuminated with a plane wave and focuses to a point in the output plane. When chirp-encoding is used this way, it results in magnification of the output measurement. This is coupled with use of a higher order focus in the output plane to yield very high output resolution.
This study is an experimental analysis of a binary joint transform based fingerprint verification system. A constant false alarm rate performance analysis is used. Correct detection of matching prints is defined as a valid pass. Correct (non)detection of unmatched prints is a valid reject. Rejection of matching prints is a false alarm, and passing unmatched prints is a false pass. In this evaluation, the probability of false alarm is fixed by the detection threshold setting, and the resulting probability of false pass is analyzed. It is shown that for print rotations up to +/- 3 degrees a false alarm rate of 1 percent can be maintained with a probability of false pass of less than 5 percent. For a smaller acceptance window on the print rotation, better performance can be obtained. Experimental and simulation data is presented.
The joint transform binarization routines of frame subtraction and Fourier plane windowing are reviewed. A binary joint transform correlator (BJTC) fingerprint verification system design based on constant false alarm rate (CFAR) processing is proposed. These techniques are used to show that a BJTC based recognition system can be designed to have very good system performance. The tradeoffs between using all or part of the joint power spectrum and between displaying one or several reference prints in the input plane are addressed through simulation. It is shown that both Fourier plane windowing and multiple reference inputs can be used to significantly improve throughput at a slight cost in system performance. A recognition system with a single reference is shown to operate with a CFAR of 1 percent and a probability of false pass of less than 1 percent through a rotation range of ±3.5 degrees. A three reference system with different rotations of the same print as references obtains the same CFAR and similar false pass performance through a range of ±6 degrees.
This paper demonstrates the use of the single lens joint transform correlator (SLJTC) to precisely determine the target location for on-axis correlation with the targets superimposed. The SLJTC is a two stage processor with an input stage identical to the chirp-encoded joint transform correlator. The first stage computes the chirp-modulated joint power spectrum. The correlation signal in the chirp-encoded joint power spectrum is an amplitude encoded lens function of Fresnel zone plate. The correlation output is in the focal plane of this zone plate. The location of the center of the zone plate is proportional to the correlation location. The magnification of the correlation plane is determined by the chirp displacement. This is used to amplify small shifts in the correlation location. The SLJTC has been experimentally demonstrated with an output plane magnification of 6.3 and a peak-to-noise ratio of 16.7 dB.
The chirp encoded joint transform correlator (JTC) with separate input planes has been demonstrated in two experiments using Michaelson and Mach-Zehnder interferometers to combine the inputs. In the first, the Fourier plane modulation characteristics of the chirp- encoded JTC was investigated by correlating two pinholes. The peak-to-noise ratio performance in this experiment was 26 dB. In the second, chirp modulation was applied to correlating one fingerprint against a set of four fingerprints. Binary ferroelectric SLMs were used as inputs and for display in the Fourier plane. A discrimination ratio of 8.1 dB was demonstrated for the chirp modulated JTC. This is a 2.3 dB improvement over the discrimination observed using the same equipment in a binary JTC arrangement.
A new binary joint transform correlator (BJTC) algorithm has been implemented which compares a target fingerprint with six reference fingerprints. The correlator uses the frame subtraction technique to achieve very dense packing of the images in this input plane. Six 128 X 64 reference prints and a target print are displayed simultaneously on a 256 X 256 input SLM. A peak-to-noise ratio (PNR) of 12.7 dB has been demonstrated experimentally, and a potential for a PNR as high as 41 dB is shown using simulation. This is compared to a PNR of 6.8 dB achieved without using frame subtraction. This demonstrates that through use of frame subtraction the input separation constraints for the BJTC are eliminated and performance is improved.
With recent advances in the state-of-the-art in spatial light modulators, the optical joint transform correlator and binary joint transform correlator are becoming practical signal processing systems. However, the performance of these devices is severely limited because of the dominance of the reference and scene autocorrelation signals in the output plane. Two major problems caused by this are false correlations between multiple targets and low correlation peak amplitudes. Two recently proposed techniques which reduced or eliminate the autocorrelation signals are Fourier plane windowing and time modulation (or frame subtraction). This paper shows how these techniques can be used separately or together to improve binary joint transform correlator performance. In simulation, the two techniques provided peak to noise improvements of 2.5 and 5.5 dB over binarization based on using a uniform threshold. The improvement gained by combining the techniques was 6.6 dB.
A major limitation on the optical joint transform correlator (JTC) is that the output plane is dominated by unwanted autocorrelation products. A new technique is proposed that uses time modulation and demodulation to separate the correlation components. Time modulation is applied to the JIG inputs, resulting in a time-modulated joint power spectrum. Demodulation of the transform plane separates the self-correlation components from the other terms. When the demodulated signal is the input to the second transform stage in the JTC the result is system peak-to-noise ratio/peak-to-secondary ratio (PNR/PSR) improvement, removal of input plane location constraints, and elimination of detection problems resulting from multiple targets. Two implementations are discussed. Using a general model for sinusoidal modulation, it is shown that amplitude, phase, and polarization modulation of the inputs all result in amplitude modulation of the correlation signals in the transform plane. The general solution is difficult to implement, because it requires temporal demodulation of the joint Fourier signal on a pixel-by-pixel basis. A more practical system results from the case of square-wave modulation, where it is shown that demodulation can be easily implemented through image subtraction using only two to four frames of data. This Fourier plane processing technique has been implemented using a binary JTC (BJTC). Performance improvement of 6 dB over the conventional BJTC is demonstrated through computer simulation and laboratory results.
One of the main factors determining the performance of a binary joint transform correlator is the method used to set the binarization threshold in the transform plane. An adaptive threshold can be set by computing the average of a small local window around each pixel. It is shown theoretically and verified experimentally that the optimum size of this window for a practical BJTC configuration is a single column wide and 3 - 5 pixels long. The detection peak amplitude in experimental runs using a local window was 2 - 4 times as large as in runs using the median of the Fourier plane as the threshold. Since these adaptive thresholds are easier to compute than the median of the entire Fourier plane, this technique can be used to improve BJTC performance while reducing system complexity.
A major limitation on the optical joint transform correlation (JTC) is that the output plane is dominated by unwanted self correlation products. Temporal encoding can be applied to the JTC to separate the correlation components in the output plane. This results in SNR/PSR improvement, removal of input plane location constraints, and elimination of the detection problems which result from multiple targets. A general implementation of this is the superheterodyne image mixer. The reference and scene input images are modulated at two different frequencies. Demodulation of the transform plane output at the sum or difference of the input frequencies results in the total separation of the correlation signals. This technique can be combined with spatial filtering to further improve system performance. For the case of square wave modulation, it is shown that both modulation and demodulation can be easily implemented. Potential performance improvement is demonstrated through computer simulation.
The performance of the optical joint transform correlator is severely degraded when multiple targets or multiple identical nontarget images in the input plane produce false peaks in the output plane. One method for overcoming this is to displace the input and or reference plane along the optical axis. This results in the true correlation peaks coming to a focus in an output plane separate from the plane where the false peaks come into focus. These planes are also separated by displacement along the optical axis. We show that this separation can be achieved by placing a simple lens system along one side of the optical path in the input side of a conventional joint transform correlator. By appropriate lens choice, any virtual displacement can be achieved. Through use of computer simulation, we show the effects of varying the virtual input displacement.
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