Warping-based Motion Artefact Compensation for Multi-Line Scan Light Field Imaging

Brosch, Nicole; Štolc, Svorad; Antensteiner, Doris

doi:10.2352/issn.2470-1173.2018.15.coimg-273

Cited by 4 publications

(4 citation statements)

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“…To maximize the robustness against occlusions, and to be able to inspect dark and glossy objects, we developed an inline Light Field (LF) acquisition setup and computational imaging algorithms, called Inline Computational Imaging (ICI) [29]: the algorithms combine depth information from the LF and the orientation of surface normals obtained by applying Photometric Stereo (PS)-algorithms to images from different illumination directions [30], [31]; applied calibration procedures and compensation for transport artifacts allow precise measurements [32], [33]. Additionally, it could be shown that the technology can be scaled to optical resolutions in the µm and sub-µm range [34].…”

Section: ) Multiview Stereo Systemsmentioning

confidence: 99%

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

et al. 2021

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Fast optical 3D inline inspection sensors are a powerful tool to advance factory automation. Many of these visual inspection tasks require high speeds, high resolutions, and repeatability. Stereo vision, photometric stereo, light sectioning, and structured light are the most common principles for inline imaging in the several micrometers to sub-millimeter resolution range. Selecting the correct sensor principle can be challenging as manufacturers' datasheets frequently use different values to describe their systems and do not stick to proposed characterizations defined by the ''Initiative Fair Data Sheet'' or the VDE/VDI standards. With the help of standardized parameters, this paper aims to compare four different measurement principles, namely AIT's own single sensor light field camera method, a structured light pattern projector, a laser triangulation sensor, and a stereo camera system, with an approximate field of view of 100 × 100mm. We demonstrate simple yet meaningful experiments to determine lateral resolution, temporal noise, and calibration accuracy to enable an objective system comparison. Additionally, the reproduction of small surface structures and an overall performance on a challenging test object is evaluated. Results show that the measurement principles partly serve different application areas. The provided methods will help end users to select the correct sensor for specific applications.INDEX TERMS Automatic optical inspection, optical imaging, measurement accuracy, measurement precision, visual inspection, inline imaging, 3D imaging.

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Section: ) Multiview Stereo Systemsmentioning

confidence: 99%

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

et al. 2021

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“…Line scans are sequences of 1D recordings typically of a scene under static conditions or of a scene with camera or object movement orthogonal to the spatial dimension. Among others, they find application in industrial quality inspection [8] and biomedical imaging [9]. There are many sources for movement artifacts in line scan recordings: In the context of moving objects, poor synchronization, or jitter in the object movement results in non-uniform sampling.…”

Section: Introductionmentioning

confidence: 99%

“…There are many sources for movement artifacts in line scan recordings: In the context of moving objects, poor synchronization, or jitter in the object movement results in non-uniform sampling. Brosch et al [8] have proposed a variational formulation to estimate the warping function in the context of movement jitter for light field line scan data to reconstruct a recording that is sampled at even intervals.…”

Section: Introductionmentioning

confidence: 99%

Fast variational alignment of non-flat 1D displacements for applications in neuroimaging

Flotho

Thinnes

Kühn

et al. 2021

Journal of Neuroscience Methods

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Section: Introductionmentioning

confidence: 99%

Fast Variational Alignment of non-flat 1D Displacements for Applications in Neuroimaging

Flotho

Thinnes

Kühn

et al. 2020

Preprint

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AbstractBackgroundIn the context of signal analysis and pattern matching, alignment of 1D signals for the comparison of signal morphologies is an important problem. For image processing and computer vision, 2D optical flow (OF) methods find wide application for motion analysis and image registration and variational OF methods have been continuously improved over the past decades.New MethodWe propose a variational method for the alignment and displacement estimation of 1D signals. We pose the estimation of non-flat displacements as an optimization problem with a similarity and smoothness term similar to variational OF estimation. To this end, we can make use of efficient optimization strategies that allow real-time applications on consumer grade hardware.ResultsWe apply our method to two applications from functional neuroimaging: The alignment of 2-photon imaging line scan recordings and the denoising of evoked and event-related potentials in single trial matrices. We can report state of the art results in terms of alignment quality and computing speeds.Existing MethodsExisting methods for 1D alignment target mostly constant displacements, do not allow native subsample precision or precise control over regularization or are slower than the proposed method.ConclusionsOur method is implemented as a MATLAB toolbox and is online available. It is suitable for 1D alignment problems, where high accuracy and high speed is needed and non-constant displacements occur.

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Warping-based Motion Artefact Compensation for Multi-Line Scan Light Field Imaging

Cited by 4 publications

References 0 publications

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

Fast variational alignment of non-flat 1D displacements for applications in neuroimaging

Fast Variational Alignment of non-flat 1D Displacements for Applications in Neuroimaging

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