63 research outputs found

    Assessment of speckle denoising filters for digital holography using subjective and objective evaluation models

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    Digital holography is an emerging imaging technique for displaying and sensing three dimensional objects. The perceived image quality of a hologram is frequently corrupted by speckle noise due to coherent illumination. Although several speckle noise reduction methods have been developed so far, there are scarce quality assessment studies to address their performance and they typically focus solely on objective metrics. However, these metrics do not reflect the visual quality perceived by a human observer. In this work, the performance of four speckle reduction algorithms, namely the nonlocal means, the Lee, the Frost and the block matching 3D filters, with varying parameterizations, were subjectively evaluated. The results were ranked with respect to the perceived image quality to obtain the mean opinion scores using pairwise comparison. The correlation between the subjective results and twenty different no-reference objective quality metrics was evaluated. The experiment indicates that block matching 3D and Lee are the preferred filters, depending on hologram characteristics. The best performing objective metrics were identified for each filter.info:eu-repo/semantics/publishedVersio

    Improving reconstructions of digital holograms

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    Digital holography is a two step process of recording a hologram on an electronic sensor and reconstructing it numerically. This thesis makes a number of contri- butions to the second step of this process. These can be split into two distinct parts: A) speckle reduction in reconstructions of digital holograms (DHs), and B) modeling and overcoming partial occlusion e®ects in reconstructions of DHs, and using occlusions to reduce the effects of the twin image in reconstructions of DHs. Part A represents the major part of this thesis. Speckle reduction forms an important step in many digital holographic applications and we have developed a number of techniques that can be used to reduce its corruptive effect in recon- structions of DHs. These techniques range from 3D filtering of DH reconstructions to a technique that filters in the Fourier domain of the reconstructed DH. We have also investigated the most commonly used industrial speckle reduction technique - wavelet filters. In Part B, we investigate the nature of opaque and non-opaque partial occlusions. We motivate this work by trying to ¯nd a subset of pixels that overcome the effects of a partial occlusion, thus revealing otherwise hidden features on an object captured using digital holography. Finally, we have used an occlusion at the twin image plane to completely remove the corrupting effect of the out-of-focus twin image on reconstructions of DHs

    Digital Hologram Image Processing

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    In this thesis we discuss and examine the contributions we have made to the field of digital hologram image processing. In particular, we will deal with the processing of numerical reconstructions of real-world three-dimensional macroscopic objects recorded by in-line digital holography. Our selection of in-line digital holography over off-axis digital holography is based primarily on resolution. There is evidence that an off-axis architecture requires approximately four times the resolution to record a hologram than an in-line architecture. The high resolution of holographic film means this is acceptable in optical holography. However, in digital holography the bandwidth of the recording medium is already severely limited and if we are to extract information from reconstructions we need the highest possible resolution which, if one cannot harness the functionality of accurately reconstructing phase, is achieved through using an in-line architecture. Two of the most significant problems encountered with reconstructions of in-line digital holograms include the small depth-of-field of each reconstruction and corruptive influence of the unwanted twin-image. This small depth-of-field makes it difficult to accurately process the numerical reconstructions and it is in this shortcoming that we will make our first three contributions: focusing algorithms, background and object segmentation algorithms and algorithms to create a single image where all object regions are in focus. Using a combination of our focusing algorithms and our background segmentation algorithm, we will make our fourth contribution: a rapid twin-image reduction algorithm for in-line digital holography. We believe that our techniques would be applicable to all digital holographic objects, in particular its relevant to objects where phase unwrapping is not an option. We demonstrate the usefulness of the algorithms for a range of macroscopic objects with varying texture and contrast

    Digital Hologram Image Processing

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    In this thesis we discuss and examine the contributions we have made to the field of digital hologram image processing. In particular, we will deal with the processing of numerical reconstructions of real-world three-dimensional macroscopic objects recorded by in-line digital holography. Our selection of in-line digital holography over off-axis digital holography is based primarily on resolution. There is evidence that an off-axis architecture requires approximately four times the resolution to record a hologram than an in-line architecture. The high resolution of holographic film means this is acceptable in optical holography. However, in digital holography the bandwidth of the recording medium is already severely limited and if we are to extract information from reconstructions we need the highest possible resolution which, if one cannot harness the functionality of accurately reconstructing phase, is achieved through using an in-line architecture. Two of the most significant problems encountered with reconstructions of in-line digital holograms include the small depth-of-field of each reconstruction and corruptive influence of the unwanted twin-image. This small depth-of-field makes it difficult to accurately process the numerical reconstructions and it is in this shortcoming that we will make our first three contributions: focusing algorithms, background and object segmentation algorithms and algorithms to create a single image where all object regions are in focus. Using a combination of our focusing algorithms and our background segmentation algorithm, we will make our fourth contribution: a rapid twin-image reduction algorithm for in-line digital holography. We believe that our techniques would be applicable to all digital holographic objects, in particular its relevant to objects where phase unwrapping is not an option. We demonstrate the usefulness of the algorithms for a range of macroscopic objects with varying texture and contrast

    Improvements in Digital Holographic Microscopy

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    The Ph.D. dissertation consists of developing a series of innovative computational methods for improving digital holographic microscopy (DHM). DHM systems are widely used in quantitative phase imaging for studying micrometer-size biological and non-biological samples. As any imaging technique, DHM systems have limitations that reduce their applicability. Current limitations in DHM systems are: i) the number of holograms (more than three holograms) required in slightly off-axis DHM systems to reconstruct the object phase information without applying complex computational algorithms; ii) the lack of an automatic and robust computation algorithm to compensate for the interference angle and reconstruct the object phase information without phase distortions in off-axis DHM systems operating in telecentric and image plane conditions; iii) the necessity of an automatic computational algorithm to simultaneously compensate for the interference angle and numerically focus out-of-focus holograms on reconstructing the object phase information without phase distortions in off-axis DHM systems operating in telecentric regime; iv) the deficiency of reconstructing phase images without phase distortions at video-rate speed in off-axis DHM operating in telecentric regime, and image plane conditions; v) the lack of an open-source library for any DHM optical configuration; and, finally, vi) the tradeoff between speckle contrast and spatial resolution existing in current computational strategies to reduce the speckle contrast. This Ph.D. dissertation is motivated to overcome or at least reduce the six limitations mentioned above. Each chapter of this dissertation presents and discusses a novel computational method from the theoretical and experimental point of view to address each of these limitations

    Computer-Generated Phase-Only Holograms for Real-Time Image Display

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    On Fresnelets, interference fringes, and digital holography

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    In this thesis, we describe new approaches and methods for reconstructing complex-valued wave fields from digital holograms. We focus on Fresnel holograms recorded in an off-axis geometry, for which operational real-time acquisition setups readily exist. The three main research directions presented are the following. First, we derive the necessary tools to port methods and concepts of wavelet-based approaches to the field of digital holography. This is motivated by the flexibility, the robustness, and the unifying view that such multiresolution procedures have brought to many applications in image processing. In particular, we put emphasis on space-frequency processing and sparse signal representations. Second, we propose to decouple the demodulation from the propagation problem, which are both inherent to digital Fresnel holography. To this end, we derive a method for retrieving the amplitude and phase of the object wave through a local analysis of the hologram's interference fringes. Third, since digital holography reconstruction algorithms involve a number of parametric models, we propose automatic adjustment methods of the corresponding parameters. We start by investigating the Fresnel transform, which plays a central role in both the modeling of the acquisition procedure and the reconstruction of complex wave fields. The study of the properties that are central to wavelet and multiresolution analysis leads us to derive Fresnelets, a new family of wavelet-like bases. Fresnelets permit the analysis of holograms with a good localization in space and frequency, in a way similar to wavelets for images. Since the relevant information in a Fresnel off-axis hologram may be separated both in space and frequency, we propose an approach for selectively retrieving the information in the Fresnelet domain. We show that in certain situations, this approach is superior to others that exclusively rely on the separation in space or frequency. We then derive a least-squares method for the estimation of the object wave's amplitude and phase. The approach, which is reminiscent of phase-shifting techniques, is sufficiently general to be applied in a wide variety of situations, including those dictated by the use of microscopy objectives. Since it is difficult to determine the reconstruction distance manually, we propose an automatic procedure. We take advantage of our separate treatment of the phase retrieval and propagation problems to come up with an algorithm that maximizes a sharpness metric related to the sparsity of the signal's expansion in distance-dependent Fresnelet bases. Based on a simulation study, we suggest a number of guidelines for deciding which algorithm to apply to a given problem. We compare existing and the newly proposed solutions in a wide variety of situations. Our final conclusion is that the proposed methods result in flexible algorithms that are competitive with preexisting ones and superior to them in many cases. Overall, they may be applied in a wide range of experimental situations at a low computational cost

    Подавление мультипликативного шума на радиолокационных изображениях

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    Introduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. The values of these parameters have to be selected experimentally. In works devoted to speckle noise filtering, the methods used for selecting filter paraments are rarely clarified.Aim. To present a methodology for selecting the parameters of multiplicative speckle noise filters on a radar image that are optimal in terms of the quality of the resulting image.Materials and methods. The article presents a method for determining the optimal parameters of speckle noise reduction filters. This method was applied to the most conventionally used filters. The search for optimal parameters and testing of the filters were carried out using a specially designed image, which contained the objects most frequently found on radar images. The structural similarity index (SSIM) metric was chosen as a metric that assesses the quality of filtration.Results. After determining the optimal (in terms of SSIM) parameters of speckle noise reduction filters, the filters were compared to select the best filters in terms of the quality of radar image processing. In addition, the operation of the filters under study was tested on images containing various types of objects, namely: large objects, small objects and sharp borders. Knowing which filter copes best with smoothing speckle noise in a particular area and what values of the variable parameters this requires, an optimal quality of radar images can be achieved. Filtering not only improves human perception of radar images, but also reduces the influence of speckle noise during their further processing (object detection, segmentation of areas, etc.).Conclusion. The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. The quality of filtration was assessed using an expert method (visually) by comparing images before and after filtration, differential images and one-dimensional image slices. The Frost filter and the anisotropic diffusion filter with optimal parameters showed the best processing quality according to the SSIM metric.Введение. Радиолокационное изображение (РЛИ) – это изображение, получаемое зондированием земной поверхности с помощью радиолокационного устройства. РЛИ обладает важной особенностью в виде спекл-шума, который вызывает зернистость фона. Данный шум необходимо фильтровать с целью улучшения качества РЛИ. Фильтры спекл-шума часто имеют в своей структуре один или несколько параметров, которые контролируют уровень сглаживания шума и значения которых приходится подбирать экспериментально. В статьях, посвященных фильтрации спекл-шума, авторы часто не поясняют, как были выбраны значения параметров фильтров.Цель работы. Представление методики для выбора оптимальных в смысле качества получаемого изображения параметров фильтров мультипликативного спекл-шума на РЛИ.Материалы и методы. Рассмотрена разработанная методика поиска оптимальных параметров фильтров спекл-шума применительно к наиболее часто используемым фильтрам. Поиск оптимальных параметров и тестирование работы фильтров проводятся на специально разработанном изображении, содержащем объекты, наиболее часто встречающиеся на РЛИ. Метрикой, оценивающей качество проведенной фильтрации, служил индекс структурного сходства SSIM (Structural Similarity Index Metric).Результаты. После нахождения оптимальных по SSIM параметров рассматриваемых фильтров проведено сравнение работы фильтров с точки зрения обработки РЛИ и найдены наилучшие фильтры для этой задачи. Также работа рассматриваемых фильтров протестирована на изображениях, содержащих различные типы объектов, а именно: большие объекты, мелкие объекты, резкие границы. Зная, какой фильтр наилучшим образом справляется со сглаживанием шума на той или иной области и какие для этого необходимы значения варьируемых параметров, можно использовать полученные результаты для фильтрации радиолокационных изображений. Фильтрация не только улучшает восприятие РЛИ человеком, но и позволяет снизить влияние спекл-шума на дальнейшую автоматизированную обработку РЛИ (детектирование объектов, сегментация областей и др.).Заключение. Предложенный алгоритм позволил найти оптимальные параметры для нескольких фильтров спекл-шума. Качество фильтрации оценивалось экспертным способом (визуально), посредством сравнения изображений до и после фильтрации, разностных изображений и одномерных срезов изображений. Фильтр Фроста и фильтр анизотропной диффузии с оптимальными параметрами показали лучшее качество обработки по SSIM
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