Awwal, A.

Bliss, E.

Leach, R.

Roberts, R. S.

Rushford, M.

Wilhelmsen, K.

UNT Digital Library

LLNL-CONF-644268Image Analysis For The AutomatedAlignment of the Advanced RadiographyCapability (ARC) Diagnostic Path#R. S. Roberts, A. Awwal, R. Leach, M. Rushford,E. Bliss, K. WilhelmsenSeptember 26, 2013ICALEPCS 2013San Francisco, CA, United StatesOctober 6, 2013 through October 11, 2013Disclaimer  This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.  Image Analysis for the Automated Alignment of the Advanced RadiographyCapability (ARC) Diagnostic Path∗Randy Roberts† , Abdul Awwal, Richard Leach, Michael Rushford,Erlan Bliss and Karl Wilhelmsen,Lawrence Livermore National Laboratory, Livermore, CA 94550, USAAbstractThe Advanced Radiographic Capability (ARC) at theNational Ignition Facility was developed to produce a se-quence of short laser pulses that are used to backlight animploding fuel capsule. This backlighting capability willenable the creation of a sequence of radiographs duringcapsule implosion and provide an unprecedented view intothe dynamics of the implosion. A critical element of theARC is the diagnostic instrumentation used to assess thequality of the pulses. Pulses are steered to the diagnosticpackage through a complex optical path that requires pre-cision alignment. A central component of the alignmentsystem is the image analysis algorithms, which are usedto extract information from alignment imagery and providefeedback for the optical alignment control loops. Align-ment imagery consists of complex patterns of light result-ing from the diffraction of pilot beams around cross-hairsand other fiducials placed in the beam path. This paperdescribes the alignment imagery for two ARC automatedalignment loops, and the image analysis algorithms usedto extract information required for the operation of thoseloops.INTRODUCTIONLaser pulses produced by the Advanced RadiographicCapability (ARC) at the National Ignition Facility (NIF)require comprehensive characterization to ensure that theymeet design specifications. To perform this characteriza-tion, selected pulses from the ARC are directed to a diag-nostic table containing a variety of instrumentation. Theoptical path that directs these pulses is complex and re-quires automated alignment of a large number of optics.The alignment process consists of manipulating mirrors tocenter and point the beams (pulses) along the optical path.Feedback loops provide inputs to actuators on the mirrormounts, and adjust the actuators to decrease the distancebetween reference and beam-position fiducials extractedfrom alignment imagery. Control loops execute two imageprocessing algorithms, one for centering the beam and onefor pointing the beam. Imagery for the centering operationis collected by a near-field camera, and imagery associatedwith pointing operations is collected by a far-field camera.Figure 1 illustrates a simplified schematic of the beam∗This work was performed under the auspices of the U.S. Departmentof Energy by Lawrence Livermore National Laboratory under ContractDE-AC52-07NA27344.† roberts38@llnl.govpath from the compressor vessels to the diagnostic ta-ble. ARC compressor vessels CV1 and CV2 each com-press pulses from two modified NIF beams using arrays ofdiffraction gratings [1]. NIF beams are directed out of CV1and CV2 toward the target chamber by the AM5 mirrors.The AM5 mirrors are partially transmitting, allowing 0.2%of each ARC beam and 70% of each pilot beam to propa-gate to its DM1 mirror. Each DM1 mirror is mounted on avertical translation stage, which enables it to reflect eitherthe upper or lower output from the associated compressorvessel. After DM1, the beams are reflected by the DM2mirrors towards calorimeters positioned behind the DM3mirrors. Beams from CV1 and CV2 are directed by theDM3 mirrors to mirror DM4. This mirror pivots to selectthe output beam from either CV1 or CV2. From there, asingle beam is directed into the diagnostic table by mirrorsDM5, DM6 and DM7.In the ARC diagnostic path, there are three sets ofpointing and centering loops that control the DM1/DM2,DM3/DM4 and DM5/DM7 mirror pairs. Near-field andfar-field cameras for these loops are positioned respectivelybehind the DM3, DM5 and on the ARC Diagnostic Ta-ble. In this paper, we describe image processing algorithmsassociated with the DM3/DM4 and DM5/DM7 centeringloops. (Space limitations preclude a discussion of all imageprocessing used to align the path from the ARC compressorvessels to the ARC diagnostic table. The DM3/DM4 andDM5/DM7 centering loops were selected for their techni-cal interest.)Pointing and centering loops DM1/DM2, DM3/DM4and DM5/DM7 are aligned using small-diameter pilotbeams positioned beneath the larger NIF/ARC beams.Three pilot beams are associated with each NIF beam, a980 nm beam straddled by two 1053 nm beams. Thesepilot beams propagate alignment references positioned atsurveyed locations along the beam path. These cross-hairsand apertures impose patterns on the intensity profiles ofthe pilot beams which serve as alignment fiducials. Forexample, cross-hairs beneath the AM5 mirrors identify thecorrect position for the pilot beams as they pass through.These crosshairs create a diffraction pattern in the pilotbeam profiles, and features in this pattern are used in subse-quent control loops. As another example, apertures placedbeneath the DM5 mirror provide centering references forbeams from the CV1 or CV2 compressor vessel for theDM3/DM4 centering loops.Development of the image processing algorithms andimplementation of ARC diagnostic path hardware are pro-Figure 1: Simplified schematic of the beam path from the ARC compressor vessels to the ARC Diagnostic Table. NIFbeams B351 and B352 are input to Compressor Vessel CV1, and beams B353 and B354 input to CV2, and a fraction ofone of these beams is switched to the ARC Diagnostic Table. Labels for the DM1—3 mirrors and calorimeter packagefor CV2 are omitted for clarity.ceeding in parallel. As a result, imagery from the actualARC hardware was not available to algorithm developers.To expedite algorithm development, synthetic imagery wascreated from optical models of the diagnostic path using theFRED Optical Engineering Software [2]. Suites of severalhundred images were created for each algorithm to sim-ulate a variety of anticipated beam and optics conditions.The algorithms and imagery presented here, along with allof the image processing algorithms in the diagnostic beampath, were developed using this imagery. When real im-agery is available from ARC hardware the image process-ing algorithms will be appropriately modified as needed.DM3/DM4 NEAR FIELD IMAGEPROCESSINGA near field image for the DM3/DM4 centering loopis shown in Figure 2a. This imagery, along with im-agery for the DM5/DM7 centering loop (presented later), is1392×1040 pixels and 12-bits deep. Two annuli, one alongthe pilot beam path from CV1 and the other along the pathfrom CV2, are placed below mirror DM5. These annuliserve as beam centering references. Note that only one an-nulus is used at a time due to beam selection by DM4. Thediffraction pattern from the AM5 crosshair in the 980 nmpilot beam has substantially decreased by this point in thebeam path, although some remnants of the pattern remain.Figure 2: Illustration of the near field image for theDM3/DM4 alignment loop. (a) near field image, (b) nearfield image annotated with the reference fiducial (red ’+’)and beam position (green ’+’).Image processing is required to estimate the center of theannulus (xa, ya) as indicated in Figure 2b by the red ’+’.(The exterior edge of the ring is outlined in red for refer-ence.) The image processing is also require to estimate thecenter of the pilot beam (xb, yb), as indicated by the green’+’ in Figure 2b. Using these two fiducials, the centeringloop manipulates mirrors DM3/DM4 to align the center ofone pilot beam (selected by DM4) with the center of itsassociated annulus.Processing of the DM3/DM4 near field image I beginswith a series of checks to detect off-normal conditions suchas excessive saturated pixels, very low contrast image, etc.See [3] for a discussion of off-normal checks. After the im-age has been screened, a 3× 3 Sobel operator is convolvedwith I to create edge image E. Projections along the x-and y-coordinates are next performed:px(j) = 〈Eij〉i (1)py(i) = 〈Eij〉j (2)where, for example, the equation px(j) = 〈Eij〉i indicatesthat the jth entry of the x-projection is found by averag-ing Eij over the columns that span row j. Edge image Eand the x- and y-projections are shown in Figure 3. Projec-tions px and py are thresholded and the resulting binarysequences are searched for zero-run-lengths that are ap-proximately as long as the number of pixels in the widthof the annulus shadow in the DM3/DM4 near field image.Denote the maximum and minimum indices of these zero-run-lengths as xr, xl, yu and yl to denote the right, left,upper and lower boundaries of the exterior edge of the an-nulus. These values provide an initial estimate of the radiusof the annulus r̃a, and the average of these values providean initial estimate of the center of the annulus (x̃a, ỹa).The initial estimate of the annulus radius r̃a is then usedto obtain a more accurate estimate of the center of the an-nulus. Circles with a range of radii C(ri) are correlatedagainst the edge detected image, and the radius correspond-ing to the maximum normalized correlation is selected asthe estimate of the location of the annulus center (x̂a, ŷa).An estimate of the beam center is provided by a simpleweighted average over the interior of the annulus:x̂b =∑m(∑n I(m,n))m∑m∑n I(m,n)ŷb =∑n(∑m I(m,n))n∑m∑y I(m,n)(3)where indices m,n are restricted to the interior region ofthe annulus. The DM3/DM4 near-field image processingalgorithm is synopsized in algorithm 1.Algorithm 1 DM3/DM4 Near Field Image Processing1: Perform off-normal checks on image I2: Convolve I with Sobel operator to produce edge imageE3: Average across rows and columns of E to create pro-jections py(·) and px(·)4: compute rough estimate exterior radius r̃a and center(x̃c, ỹc) of annulus5: Refine estimate of radius and center of annulus by cor-relating I with circular kernels C(ri) over a range ofradii ri6: Estimate annulus center (x̂c, ŷc) as the location of thecorrelation peak7: Estimate beam center (x̂b, ŷb) as the weighted centroidof the interior region of the annulusFigure 3: DM3/DM4 near field edge detection image andx- and y-projections of the edges.Figure 4: Illustration of the near field image of theDM5/DM7 centering loop. (a) Pattern created by the1053 nm pilot beam and the AM5 cross-hair. (b) Enlargedview of the pattern annotated with the ’+’ pattern (greendashed lines) and the center of the pattern (green ’x’).DM5/DM7 NEAR FIELD IMAGEPROCESSINGThe near field image of the DM5/DM7 alignment loopis imaged on a camera on the ARC Diagnostic Table andappears as an image of the AM5 crosshair back-lit by thepilot beam. The region of support of the pattern is tiny(approximately 25 × 25 pixels, see Figure 4a), and an en-largement of the pattern is shown in Figure 4b. The imageprocessing is required to estimate the location of the cen-ter of the crosshair. This point is roughly described as thecenter of the ’+’ shaped shadow within the illuminated re-gion of the pattern. The centering loop manipulates mirrorsDM5/DM7 to align this fiducial with a predefined point onthe near field camera.The DM5/DM7 near field image I is first processedthough several off-normal checks as previously describedfor the DM3/DM4 near field image. After off-normalchecks, the image is processed in two steps: an initial esti-mate of the fiducial location is obtained and then later re-fined. To begin, image I is converted to binary image BFigure 5: Image processing for the Near field image forthe DM5/DM7 centering loop. (a) DM5/DM7 near fieldimage, (b) projection in the x direction (red line indicatessmoothed projection), (c) the first (smoothed) difference,(d) second smoothed difference.by applying a threshold followed by morphological fill op-erations. The largest connected region R in image B isfound, and the weighted centroid (x̃c, ỹc) of these pixels iscomputed (cf. Equation 3). A mask is created by defin-ing a circular region large enough to contain the region ofsupport of the pattern centered at (x̃c, ỹc). Image I is mul-tiplied by this mask to create image M . This completes thecalculation of the initial center estimate in the first phase ofthe algorithm.In the second phase, (x̃c, ỹc) is refined by a processof projection and smoothed differencing. The rows andcolumns of masked image M are projected to form meanprojections px(j) = 〈Mij〉i and py(i) = 〈Mij〉j . The pro-jections contain information on the slope of the illumina-tion pattern, which in turn is used used to estimate the lo-cation of the fiducial. Each projection is differenced andsmoothed twice to provide the second difference of the im-age projections. For example, the first smoothed-differencep′y is found from projection py as:p′y = [py(1)− py(0), . . . , py(N − 1)− py(N − 2))] ∗Ws(4)where Ws is a smoothing kernel applied to the differencesequence. In a similar manner, second difference p′′y isfound from p′y . The locations of the peaks of the smoothedsecond-difference projections provide a refined estimate ofthe fiducial location. See Figure 5 for exemplar plots of theprojections.While many interpolation approaches are available forlocating the position of a peak, a simple and robust schemewas used here. The set of indices P is formed from thesmoothed second-difference projections where each indexis associated with an amplitude that is greater than thresh-old Ta =√(2)/2 times the peak value in the projection.For example, for the y-projection we have the set of in-dices:Py := {i|p′′y(i) ≥ Ta ∗max(p′′y(i)} (5)In this case, the refined estimate of the y-coordinate forthe fiducial is average of the indices in set Py: ŷ = 〈Py〉.In a similar manner, the estimate for the x-coordinate forthe fiducial is found as the average of indices in set Px:x̂ = 〈Px〉. The DM5/DM7 near field image processingalgorithm is synopsized in Algorithm 2.Algorithm 2 DM5/DM7 Near Field Image Processing1: Perform off-normal checks on image I2: Create binary image: [I]T → B3: Locate largest connected region R in image B4: Calculate weighted centroid of pixels (x̃c, ỹc) withinregion I(R)5: Define circle region surrounding (x̃c, ỹc). Use this re-gion to mask image I and create masked image M6: Average across rows and columns of M to create pro-jections py(·) and px(·)7: Compute smoothed difference projections p′′y and p′′x8: Refine estimate of fiducial location (x̃c, ỹc) to (x̂, ŷ)using peak locations in smoothed second differenceprojections py(·) and px(·)SUMMARYWe have developed a set of image processing algorithmsthat are used in control loops that align the beam path fromthe ARC compressor vessels to the ARC Diagnostic Table.Two of those algorithms were presented here. These al-gorithms were developed using suites of synthetic imagerycreated by optics modeling software. Algorithm develop-ment using synthetic imagery has allowed us to greatly re-duce the amount of time required to deploy the algorithmsto hardware. Algorithm performance will be fully assessedwhen implementation of the ARC diagnostic path hardwareis fully implemented and qualified.REFERENCES[1] Crane, J. K., et al. “Progress on converting a NIF quad toeight, petawatt beams for advanced radiography.” Journal ofPhysics: Conference Series. Vol. 244. No. 3. IOP Publishing,2010.[2] “FRED Software.” Internet: www.photonengr.com/software/,[9 Sept 2013].[3] J.V. Candy, et al., “Detection of off-normal images for NIFautomatic alignment”, in: K. Iftekharuddin, A.A.S. Awwal(Eds.), Photonic Devices and Algorithms for Computing VII,Proc. of SPIE, vol. 5907, p.59070B, 2005.

Image Analysis For The Automated Alignment of the Advanced Radiography Capability (ARC) Diagnostic Path

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Image Analysis For The Automated Alignment of the Advanced Radiography Capability (ARC) Diagnostic Path

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