403 research outputs found

    A Bayesian Hyperprior Approach for Joint Image Denoising and Interpolation, with an Application to HDR Imaging

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    Recently, impressive denoising results have been achieved by Bayesian approaches which assume Gaussian models for the image patches. This improvement in performance can be attributed to the use of per-patch models. Unfortunately such an approach is particularly unstable for most inverse problems beyond denoising. In this work, we propose the use of a hyperprior to model image patches, in order to stabilize the estimation procedure. There are two main advantages to the proposed restoration scheme: Firstly it is adapted to diagonal degradation matrices, and in particular to missing data problems (e.g. inpainting of missing pixels or zooming). Secondly it can deal with signal dependent noise models, particularly suited to digital cameras. As such, the scheme is especially adapted to computational photography. In order to illustrate this point, we provide an application to high dynamic range imaging from a single image taken with a modified sensor, which shows the effectiveness of the proposed scheme.Comment: Some figures are reduced to comply with arxiv's size constraints. Full size images are available as HAL technical report hal-01107519v5, IEEE Transactions on Computational Imaging, 201

    An Improved Observation Model for Super-Resolution under Affine Motion

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    Super-resolution (SR) techniques make use of subpixel shifts between frames in an image sequence to yield higher-resolution images. We propose an original observation model devoted to the case of non isometric inter-frame motion as required, for instance, in the context of airborne imaging sensors. First, we describe how the main observation models used in the SR literature deal with motion, and we explain why they are not suited for non isometric motion. Then, we propose an extension of the observation model by Elad and Feuer adapted to affine motion. This model is based on a decomposition of affine transforms into successive shear transforms, each one efficiently implemented by row-by-row or column-by-column 1-D affine transforms. We demonstrate on synthetic and real sequences that our observation model incorporated in a SR reconstruction technique leads to better results in the case of variable scale motions and it provides equivalent results in the case of isometric motions

    CHARACTERIZATION OF SEED DEFECTS IN HIGHLY SPECULAR SMOOTH COATED SURFACES

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    Many smooth, highly specular coatings such as automotive paints are subjected to considerable performance demands as the customer expectations for appearance of coatings are continually increasing. Therefore it is vital to develop robust methods to monitor surface quality online. An automated visual assessment of specular coated surface that would not only provide a cost effective and reliable solution to the industries but also facilitate the implementation of a real-time feedback loop. The scope of this thesis is a subset of the inspection technology that facilitates real-time close loop control of the surface quality and concentrates on one common surface defect the seed defect. This machine vision system design utilizes surface reflectance models as a rational basis. Using a single high-contrast image the height of the seed defect is computed; the result is obtained rapidly and is reasonably accurate approximation of the actual height

    Lightfield Analysis and Its Applications in Adaptive Optics and Surveillance Systems

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    An image can only be as good as the optics of a camera or any other imaging system allows it to be. An imaging system is merely a transformation that takes a 3D world coordinate to a 2D image plane. This can be done through both linear/non-linear transfer functions. Depending on the application at hand it is easier to use some models of imaging systems over the others in certain situations. The most well-known models are the 1) Pinhole model, 2) Thin Lens Model and 3) Thick lens model for optical systems. Using light-field analysis the connection through these different models is described. A novel figure of merit is presented on using one optical model over the other for certain applications. After analyzing these optical systems, their applications in plenoptic cameras for adaptive optics applications are introduced. A new technique to use a plenoptic camera to extract information about a localized distorted planar wave front is described. CODEV simulations conducted in this thesis show that its performance is comparable to those of a Shack-Hartmann sensor and that they can potentially increase the dynamic range of angles that can be extracted assuming a paraxial imaging system. As a final application, a novel dual PTZ-surveillance system to track a target through space is presented. 22X optic zoom lenses on high resolution pan/tilt platforms recalibrate a master-slave relationship based on encoder readouts rather than complicated image processing algorithms for real-time target tracking. As the target moves out of a region of interest in the master camera, it is moved to force the target back into the region of interest. Once the master camera is moved, a precalibrated lookup table is interpolated to compute the relationship between the master/slave cameras. The homography that relates the pixels of the master camera to the pan/tilt settings of the slave camera then continue to follow the planar trajectories of targets as they move through space at high accuracies

    Determining Bulk Aerosol Absorption from Off Axis Backscattering using Rayleigh Beacon Laser Pulses

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    Aerosol absorption and scattering can play a key role in degrading high energy laser performance in the form of thermal blooming and beam attenuation. Aerosol absorption properties are not completely understood, and thus affect how we are able to quantify expected high energy laser weapon performance. The Air Force Institute of Technology Center for Directed Energy (AFIT CDE) developed both Laser Environmental Effects Definition and Reference (LEEDR) and the High Energy Laser End-to-End Operational Simulation (HELEEOS) code to characterize atmospheric radiative transfer effects and evaluate expected directed energy weapon system performance. These packages enable modeling of total irradiance at given off-axis locations through the use of an off-axis scattering algorithm, which uses scattering phase functions to predict the amount of radiation scattered from the beam toward a particular observation location. Laser energy scattered from a Rayleigh beacon illuminator at 527 nm, located at the John Bryan Observatory (JBO) in Yellow Springs, Ohio, is measured using a high resolution Mini- Shortwave Infrared (SWIR) snapshot camera. Aerosol characterization information was gathered using a Condensation Particle Counter (CPC), a Scanning Mobility Particle Sizer (SMPS) spectrometer, and a Continuous Light Absorption Photometer (CLAP). The differences in the measured versus predicted phase functions can help draw conclusions relative to bulk aerosol absorption properties, and lead to better quantification of degradation of laser performance due to aerosols

    Luminescence digital imaging microscopy.

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    A novel compact Shearographic NDT system

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    Includes bibliographical referencesThere is a need in industry and the NDT (Non-destructive Testing) community for quick, reliable, user-friendly and cost-effective compact NDT systems that can be used on a wide variety of materials and structures, for quality assurance and maintenance. Designing and building a compact Shearographic NDT system will enhance the capability of inspection during quality assurance and maintenance routines as well as reduce inspection time. Older compact Shearographic systems, which have been tested satisfactorily both under laboratory and field conditions at the NDT Laboratory at the University of Cape Town, have a rather restricted field of view. This is due to the proprietary shearing optics being placed in front of the camera lens, which in other words means that the field of view can only be increased by using a relatively small focal length camera lens which results in having to increase the size of the shearing optics. This would make the compact Shearographic device much larger which is counter-productive since technology enables/directs research and development toward more compact devices

    Guided direct time-of-flight Lidar for self-driving vehicles

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    Self-driving vehicles demand efficient and reliable depth-sensing technologies. Lidar, with its capacity for long-distance, high-precision measurement, is a crucial component in this pursuit. However, conventional mechanical scanning implementations suffer from reliability, cost, and frame rate limitations. Solid-state lidar solutions have emerged as a promising alternative, but the vast amount of photon data processed and stored using conventional direct time-of-flight (dToF) prevents long-distance sensing unless power-intensive partial histogram approaches are used. This research introduces a pioneering ‘guided’ dToF approach, harnessing external guidance from other onboard sensors to narrow down the depth search space for a power and data-efficient solution. This approach centres around a dToF sensor in which the exposed time widow of independent pixels can be dynamically adjusted. A pair of vision cameras are used in this demonstrator to provide the guiding depth estimates. The implemented guided dToF demonstrator successfully captures a dynamic outdoor scene at 3 fps with distances up to 75 m. Compared to a conventional full histogram approach, on-chip data is reduced by over 25 times, while the total laser cycles in each frame are reduced by at least 6 times compared to any partial histogram approach. The capability of guided dToF to mitigate multipath reflections is also demonstrated. For self-driving vehicles where a wealth of sensor data is already available, guided dToF opens new possibilities for efficient solid-state lidar

    Underwater image restoration: super-resolution and deblurring via sparse representation and denoising by means of marine snow removal

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    Underwater imaging has been widely used as a tool in many fields, however, a major issue is the quality of the resulting images/videos. Due to the light's interaction with water and its constituents, the acquired underwater images/videos often suffer from a significant amount of scatter (blur, haze) and noise. In the light of these issues, this thesis considers problems of low-resolution, blurred and noisy underwater images and proposes several approaches to improve the quality of such images/video frames. Quantitative and qualitative experiments validate the success of proposed algorithms
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