850 research outputs found

    Physics-Informed Computer Vision: A Review and Perspectives

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    Incorporation of physical information in machine learning frameworks are opening and transforming many application domains. Here the learning process is augmented through the induction of fundamental knowledge and governing physical laws. In this work we explore their utility for computer vision tasks in interpreting and understanding visual data. We present a systematic literature review of formulation and approaches to computer vision tasks guided by physical laws. We begin by decomposing the popular computer vision pipeline into a taxonomy of stages and investigate approaches to incorporate governing physical equations in each stage. Existing approaches in each task are analyzed with regard to what governing physical processes are modeled, formulated and how they are incorporated, i.e. modify data (observation bias), modify networks (inductive bias), and modify losses (learning bias). The taxonomy offers a unified view of the application of the physics-informed capability, highlighting where physics-informed learning has been conducted and where the gaps and opportunities are. Finally, we highlight open problems and challenges to inform future research. While still in its early days, the study of physics-informed computer vision has the promise to develop better computer vision models that can improve physical plausibility, accuracy, data efficiency and generalization in increasingly realistic applications

    Improvements in the registration of multimodal medical imaging : application to intensity inhomogeneity and partial volume corrections

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    Alignment or registration of medical images has a relevant role on clinical diagnostic and treatment decisions as well as in research settings. With the advent of new technologies for multimodal imaging, robust registration of functional and anatomical information is still a challenge, particular in small-animal imaging given the lesser structural content of certain anatomical parts, such as the brain, than in humans. Besides, patient-dependent and acquisition artefacts affecting the images information content further complicate registration, as is the case of intensity inhomogeneities (IIH) showing in MRI and the partial volume effect (PVE) attached to PET imaging. Reference methods exist for accurate image registration but their performance is severely deteriorated in situations involving little images Overlap. While several approaches to IIH and PVE correction exist these methods still do not guarantee or rely on robust registration. This Thesis focuses on overcoming current limitations af registration to enable novel IIH and PVE correction methods.El registre d'imatges mèdiques té un paper rellevant en les decisions de diagnòstic i tractament clíniques així com en la recerca. Amb el desenvolupament de noves tecnologies d'imatge multimodal, el registre robust d'informació funcional i anatòmica és encara avui un repte, en particular, en imatge de petit animal amb un menor contingut estructural que en humans de certes parts anatòmiques com el cervell. A més, els artefactes induïts pel propi pacient i per la tècnica d'adquisició que afecten el contingut d'informació de les imatges complica encara més el procés de registre. És el cas de les inhomogeneïtats d'intensitat (IIH) que apareixen a les RM i de l'efecte de volum parcial (PVE) característic en PET. Tot i que existeixen mètodes de referència pel registre acurat d'imatges la seva eficàcia es veu greument minvada en casos de poc solapament entre les imatges. De la mateixa manera, també existeixen mètodes per la correcció d'IIH i de PVE però que no garanteixen o que requereixen un registre robust. Aquesta tesi es centra en superar aquestes limitacions sobre el registre per habilitar nous mètodes per la correcció d'IIH i de PVE

    Advanced Image Acquisition, Processing Techniques and Applications

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    "Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution

    Performance Advantages of Maximum Likelihood Methods in PRBS-Modulated Time-of-flight Energy Loss Spectroscopy

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    This thesis describes the design, experimental performance, and theoretical simulation of a novel time-of-flight analyzer that was integrated into a high resolution electron energy loss spectrometer (TOF-HREELS). First we examined the use of an interleaved comb chopper for chopping a continuous electron beam. Both static and dynamic behaviors were simulated theoretically and measured experimentally, with very good agreement. The finite penetration of the field beyond the plane of the chopper leads to non-ideal chopper response, which is characterized in terms of an energy corruption effect and a lead or lag in the time at which the beam responds to the chopper potential. Second we considered the recovery of spectra from pseudo-random binary sequence (PRBS) modulated TOF-HREELS data. The effects of the Poisson noise distribution and the non-ideal behavior of the interleaved comb chopper were simulated. We showed, for the first time, that maximum likelihood methods can be combined with PRBS modulation to achieve resolution enhancement, while properly accounting for the Poisson noise distribution and artifacts introduced by the chopper. Our results indicate that meV resolution, similar to that of modern high resolution electron energy loss spectrometers, can be achieved with a dramatic performance advantage over conventional, serial detection analyzers. To demonstrate the capabilities of the TOF-HREELS instrument, we made measurements on a highly oriented thin film polytetrafluoroethylene (PTFE) sample. We demonstrated that the TOF-HREELS can achieve a throughput advantage of a factor of 85 compared to the conventional HREELS instrument. Comparisons were made between the experimental results and theoretical simulations. We discuss various factors which affect inversion of PRBS modulated Time of Flight (TOF) data with the Lucy algorithm. Using simulations, we conclude that the convolution assumption was good under the conditions of our experiment. The chopper rise time, Poisson noise, and artifacts of the chopper response are evaluated. Finally, we conclude that the maximum likelihood algorithms are able to gain a multiplex advantage in PRBS modulation, despite the Poisson noise in the detector

    Image enhancement techniques applied to solar feature detection

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    This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical union of directional filtering results, the remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed techniques can achieve excellent results in detecting large filaments and good detection rates for small filaments. The final chapter discusses proposed directions of the future research and applications to other areas of solar image processing, in particular to detection of solar flares, plages and sunspots

    Discovery of a Ringlike Dark Matter Structure in the Core of the Galaxy Cluster Cl 0024+17

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    We present a comprehensive mass reconstruction of the rich galaxy cluster Cl 0024+17 at z~0.4 from ACS data, unifying both strong- and weak-lensing constraints. The weak-lensing signal from a dense distribution of background galaxies (~120 per square arcmin) across the cluster enables the derivation of a high-resolution parameter-free mass map. The strongly-lensed objects tightly constrain the mass structure of the cluster inner region on an absolute scale, breaking the mass-sheet degeneracy. The mass reconstruction of Cl 0024+17 obtained in such a way is remarkable. It reveals a ringlike dark matter substructure at r~75" surrounding a soft, dense core at r~50". We interpret this peculiar sub-structure as the result of a high-speed line-of-sight collision of two massive clusters 1-2 Gyr ago. Such an event is also indicated by the cluster velocity distribution. Our numerical simulation with purely collisionless particles demonstrates that such density ripples can arise by radially expanding, decelerating particles that originally comprised the pre-collision cores. Cl 0024+17 can be likened to the bullet cluster 1E0657-56, but viewed alongalong the collision axis at a much later epoch. In addition, we show that the long-standing mass discrepancy for Cl 0024+17 between X-ray and lensing can be resolved by treating the cluster X-ray emission as coming from a superposition of two X-ray systems. The cluster's unusual X-ray surface brightness profile that requires a two isothermal sphere description supports this hypothesis.Comment: To appear in the June 1 issue of The Astrophysical Journa

    High Quality 3D Shape Reconstruction via Digital Refocusing and Pupil Apodization in Multi-wavelength Holographic Interferometry.

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    Multi-wavelength holographic interferometry (MWHI) has good potential for evolving into a high quality 3D shape reconstruction technique. There are several remaining challenges, including 1) depth-of-field limitation, leading to axial dimension inaccuracy of out-of-focus objects; and 2) smearing from shiny smooth objects to their dark dull neighbors, generating fake measurements within the dark area. This research is motivated by the goal of developing an advanced optical metrology system that provides accurate 3D profiles for target object or objects of axial dimension larger than the depth-of-field, and for objects with dramatically different surface conditions. The idea of employing digital refocusing in MWHI has been proposed as a solution to the depth-of-field limitation. One the one hand, traditional single wavelength refocusing formula is revised to reduce sensitivity to wavelength error. Investigation over real example demonstrates promising accuracy and repeatability of reconstructed 3D profiles. On the other hand, a phase contrast based focus detection criterion is developed especially for MWHI, which overcomes the problem of phase unwrapping. The combination for these two innovations gives birth to a systematic strategy of acquiring high quality 3D profiles. Following the first phase contrast based focus detection step, interferometric distance measurement by MWHI is implemented as a next step to conduct relative focus detection with high accuracy. This strategy results in ±100mm 3D profile with micron level axial accuracy, which is not available in traditional extended focus image (EFI) solutions. Pupil apodization has been implemented to address the second challenge of smearing. The process of reflective rough surface inspection has been mathematically modeled, which explains the origin of stray light and the necessity of replacing hard-edged pupil with one of gradually attenuating transmission (apodization). Metrics to optimize pupil types and parameters have been chosen especially for MWHI. A Gaussian apodized pupil has been installed and tested. A reduction of smearing in measurement result has been experimentally demonstrated.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91461/1/xulium_1.pd

    Digital Image Processing

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    Newspapers and the popular scientific press today publish many examples of highly impressive images. These images range, for example, from those showing regions of star birth in the distant Universe to the extent of the stratospheric ozone depletion over Antarctica in springtime, and to those regions of the human brain affected by Alzheimer’s disease. Processed digitally to generate spectacular images, often in false colour, they all make an immediate and deep impact on the viewer’s imagination and understanding. Professor Jonathan Blackledge’s erudite but very useful new treatise Digital Image Processing: Mathematical and Computational Methods explains both the underlying theory and the techniques used to produce such images in considerable detail. It also provides many valuable example problems - and their solutions - so that the reader can test his/her grasp of the physical, mathematical and numerical aspects of the particular topics and methods discussed. As such, this magnum opus complements the author’s earlier work Digital Signal Processing. Both books are a wonderful resource for students who wish to make their careers in this fascinating and rapidly developing field which has an ever increasing number of areas of application. The strengths of this large book lie in: • excellent explanatory introduction to the subject; • thorough treatment of the theoretical foundations, dealing with both electromagnetic and acoustic wave scattering and allied techniques; • comprehensive discussion of all the basic principles, the mathematical transforms (e.g. the Fourier and Radon transforms), their interrelationships and, in particular, Born scattering theory and its application to imaging systems modelling; discussion in detail - including the assumptions and limitations - of optical imaging, seismic imaging, medical imaging (using ultrasound), X-ray computer aided tomography, tomography when the wavelength of the probing radiation is of the same order as the dimensions of the scatterer, Synthetic Aperture Radar (airborne or spaceborne), digital watermarking and holography; detail devoted to the methods of implementation of the analytical schemes in various case studies and also as numerical packages (especially in C/C++); • coverage of deconvolution, de-blurring (or sharpening) an image, maximum entropy techniques, Bayesian estimators, techniques for enhancing the dynamic range of an image, methods of filtering images and techniques for noise reduction; • discussion of thresholding, techniques for detecting edges in an image and for contrast stretching, stochastic scattering (random walk models) and models for characterizing an image statistically; • investigation of fractal images, fractal dimension segmentation, image texture, the coding and storing of large quantities of data, and image compression such as JPEG; • valuable summary of the important results obtained in each Chapter given at its end; • suggestions for further reading at the end of each Chapter. I warmly commend this text to all readers, and trust that they will find it to be invaluable. Professor Michael J Rycroft Visiting Professor at the International Space University, Strasbourg, France, and at Cranfield University, England

    A Case Study of Low-Mass Star Formation

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    This article synthesizes observational data from an extensive program aimed toward a comprehensive understanding of star formation in a low-mass star-forming molecular cloud. New observations and published data spanning from the centimeter wave band to the near infrared reveal the high and low density molecular gas, dust, and pre-main sequence stars in L1551.Comment: 24 pages, 21 figures, ApJS accepte
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