High-speed Phase Recovery Using Chromatic Transport of Intensity Computation in Graphics Processing Units

Loomis, Nick; Waller, Laura; Barbastathis, George

doi:10.1364/biomed.2010.jma7

Cited by 7 publications

(13 citation statements)

References 12 publications

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“…Its experimental simplicity makes it amenable to existing microscopes in optical [1][2][3][4][5][6], x-ray [7,8], and electron [9][10][11] imaging. Subwavelength phase accuracy and real-time processing [12] are routinely achieved and errors can be reduced with multiple images [5,13,14]. One particularly convenient advantage of the TIE method is that it is fairly robust under partially coherent illumination [15,16], making it suitable for lithography aerial imaging tools, which we use here.…”

Section: Introductionmentioning

confidence: 99%

Transport of intensity phase imaging in the presence of curl effects induced by strongly absorbing photomasks

et al. 2014

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We report theoretical and experimental results for imaging of electromagnetic phase edge effects in lithography photomasks. Our method starts from the transport of intensity equation (TIE), which solves for phase from through-focus intensity images. Traditional TIE algorithms make an implicit assumption that the underlying in-plane power flow is curl-free. Motivated by our current study, we describe a practical situation in which this assumption breaks down. Strong absorption gradients in mask features interact with phase edges to contribute a curl to the in-plane Poynting vector, causing severe artifacts in the phase recovered. We derive how curl effects are coupled into intensity measurements and propose an iterative algorithm that not only corrects the artifacts, but also recovers missing curl components.

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Section: Introductionmentioning

confidence: 99%

Transport of intensity phase imaging in the presence of curl effects induced by strongly absorbing photomasks

et al. 2014

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“…Thus, phase is directly recovered from a measurement of / I z ∂ ∂ , which can be estimated from just two images taken at different defocus distances (by simply moving the camera axially). The TIE is well-posed and gives a direct solution for phase that can be computed in real-time using Fourier-based Poisson solvers [19] on a Graphics Processing Unit (GPU) [20]. However, the intensity derivative must be measured by finite difference methods, and so suffers from inaccuracies due to nonlinearity (upon large defocus) and is unstable with noise [21].…”

Section: Transport Of Intensitymentioning

confidence: 99%

Phase imaging with partially coherent light

Waller

2013

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XX

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“…For example, multiple views of the same object could be stored into one hologram. It should be noted that spatial multiplexing using color has appeared in the literature for both digital holography [207], [308] and quantitative phase retrieval [404], [405], [406], [229], so the concept is not necessarily novel but still useful.…”

Section: Digital Multiplexing Holographymentioning

confidence: 99%

“…A large list of projects using CUDA for general purpose scienti…c work has appeared since that time, including a number of projects in optics [229], [331], [332].…”

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confidence: 99%

Computational imaging and automated identification for aqueous environments

Loomis¹

2011

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Sampling the vast volumes of the ocean requires tools capable of observing from a distance while retaining detail necessary for biology and ecology, ideal for optical methods. Algorithms that work with existing SeaBED AUV imagery are developed, including habitat classi…cation with bag-of-words models and multi-stage boosting for rock…sh detection. Methods for extracting images of …sh from videos of longline operations are demonstrated.A prototype digital holographic imaging device is designed and tested for quantitative in situ microscale imaging. Theory to support the device is developed, including particle noise and the e¤ects of motion. A Wigner-domain model provides optimal settings and optical limits for spherical and planar holographic references.Algorithms to extract the information from real-world digital holograms are created. Focus metrics are discussed, including a novel focus detector using local Zernike moments. Two methods for estimating lateral positions of objects in holograms without reconstruction are presented by extending a summation kernel to spherical references and using a local frequency signature from a Riesz transform. A new metric for quickly estimating object depths without reconstruction is proposed and tested. An example application, quantifying oil droplet size distributions in an underwater plume, demonstrates the e¢ cacy of the prototype and algorithms. Course work at MIT and WHOI was helpful throughout this thesis. In particular, course materials and projects from Dr. Antonio Torralba (computer vision, detection, and boosting), Dr. Frédo Durand (computational imaging, segmentation, and probability), Dr. Rosalind Picard (machine learning, pattern recognition, and probability), Dr. Alan 4 Edelman (parallel computing and algorithms), and Dr. Barbastathis (optical systems) are re ‡ected directly, in several cases extended after the course to become complete sections of this thesis.The MIT Museum has provided unique outreach opportunities for the ideas presented in this thesis. Seth Riskin originally involved our lab in holography activities at the MIT Museum, then Kurt Hasselbalch later proposed and guided the development of an interactive display on plankton holography. The computational approaches I learned for the museum display led to further scienti…c development and spurred the use of GPUs for processing; Section 3.3.5 is a direct consequence, as is the majority of the data processing performed throughout this thesis.In reference to data processing, Matlab/MEX and NVIDIA's CUDA have been daily cornerstones for which I am continually thankful. Finally, mad props go to Dr. José "Pepe" Domínguez-Caballero, the most in ‡uential 5 person in my scienti…c development while at MIT. Pepe taught me digital holography and worked one-on-one with me throughout the beginning of my grad student career. He continued to be involved as a fellow holographer, a mentor, and a friend, discussing ideas, encouraging active experimentation, maintaining a curiosity about optics, and o¤ering eno...

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High-speed Phase Recovery Using Chromatic Transport of Intensity Computation in Graphics Processing Units

Abstract: Quantitative phase measurements are derived from the wavelength-dependent transport of intensity equation. A dispersive optical system is used with a Bayer-filtered detector and graphics processing units to record and calculate the phase in real-time.

Cited by 7 publications

References 12 publications

Transport of intensity phase imaging in the presence of curl effects induced by strongly absorbing photomasks

Transport of intensity phase imaging in the presence of curl effects induced by strongly absorbing photomasks

Phase imaging with partially coherent light

Computational imaging and automated identification for aqueous environments

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