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Advancements in optical, computing, and electronic technologies have enabled holograms of physical three-dimensional (3D) objects to be captured. The hologram can be displayed with a spatial light modulator to reconstruct a visible image. Although holography is an ideal solution for recording 3D images, a hologram comprises high-frequency fringe patterns that are almost impossible to recognize with traditional computer vision methods. Recently, it has been shown that holograms can be classified with deep learning based on convolution neural networks. However, the method can only achieve a high success classification rate if the image represented in the hologram is without speckle noise and occlusion. Minor occlusion of the image generally leads to a substantial drop in the success rate. This paper proposes a method known as ensemble deep-learning invariant occluded hologram classification to overcome this problem. The proposed new method attains over 95% accuracy in the classification of holograms of partially occluded handwritten numbers contaminated with speckle noise. To achieve the performance, a new augmentation scheme and a new enhanced ensemble structure are necessary. The new augmentation process includes occluded objects and simulates the worst-case scenario of speckle noise.
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Aprendizado Profundo , Holografia , Holografia/métodos , Redes Neurais de ComputaçãoRESUMO
A sampled phase-only hologram (SPOH) is the phase component of the hologram of an object image with pixels being sampled with a periodic grid-cross pattern. The reconstructed image of a SPOH is a sparse image with abundant empty voids and degradation in sharpness and contrast. In this paper we proposed a method based on a new sampling scheme, together with stochastic binary search (SBS), to obtain an optimal sampling lattice that can be applied to generate phase-only holograms with enhanced reconstructed image. Experimental results show that with our proposed method, the fidelity and quality of the reconstructed image are increased.
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Recently, a method known as "ensemble deep learning invariant hologram classification" (EDL-IHC) for classifying of holograms of deformable objects with deep learning network (DLN) has been demonstrated. However DL-IHC requires substantial computational resources to attain near perfect success rate (≥99%). In practice, it is always desirable to have higher success rate with a low complexity DLN. In this paper we propose a low complexity DLN known as "ensemble deep learning invariant hologram classification" (EDL-IHC). In comparison with DL-IHC, our proposed hologram classifier has promoted the success rate by 2.86% in the classification of holograms of handwritten numerals.
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A fast and non-iterative method for generating a phase-only hologram, hereafter referred to as the patterned-phase-only hologram (PPOH), is reported in this paper. Briefly, a phase mask with a periodic phase pattern is added to the source image, and converted into a hologram. Subsequently, only the phase component is retained as a phase-only hologram. Experimental evaluation reveals that the visual quality of the reconstructed images of the PPOH generated with our proposed method is favorable, and superior to that obtained with existing methods.
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If an image is uniformly down-sampled into a sparse form and converted into a hologram, the phase component alone will be adequate to reconstruct the image. However, the appearance of the reconstructed image is degraded with numerous empty holes. In this paper, we present a low complexity and non-iterative solution to this problem. Briefly, two phase-only holograms are generated for an image, each based on a different down-sampling lattice. Subsequently, the holograms are displayed alternately at high frame rate. The reconstructed images of the 2 holograms will appear to be a single, densely sampled image with enhance visual quality.
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Incoherent digital holography (IDH) can be realized by optical scanning holography or self-interference incoherent holography. Although IDH can exhibit high quality reconstruction due to its inherently speckle-free property, direct display of an incoherent hologram is a challenge because of its amplitude nonlinearity and the demand of complex modulation. In this paper we propose to compensate the amplitude nonlinearity at the object plane, and use bidirectional error-diffusion method to convert the complex-type incoherent Fresnel hologram to a phase-only Fresnel hologram for display. A spatial light modulator is used to reconstruct the phase-only hologram optically to demonstrate the validity of our proposed method.
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This paper reports a fast method for generating a 2048x2048 digital Fresnel hologram at a rate of over 100 frames per second. Briefly, the object wave of an image is nonuniformally sampled and generated on a wavefront recording plane (WPR) that is close to the object scene. The sampling interval at each point on the WRP image is then modulated according to the depth map. Subsequently, the WRP image is converted into a hologram. The hologram generated with our proposed method, which is referred to as the warped WRP (WWRP) hologram, is capable of presenting a 3-D object with faster speed as compared with existing methods.
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We present a novel non-iterative method for generating phase-only Fresnel holograms. The intensity image of the source object scene is first down-sampled with uniform grid-cross lattices. A Fresnel hologram is then generated from the intensity and the depth information of the sampled object points. Subsequently, only the phase component of the hologram is preserved, resulting in a pure phase hologram that we call the sampled-phase-only hologram (SPOH). Experimental evaluation reveals that the numerical, as well as the optical reconstructed images of the proposed phase-only hologram derived with our method are of high visual quality. Moreover, the reconstructed optical image is brighter, and less affected by phase noise contamination on the hologram as compared with those generated with existing error-diffusion approaches.
Assuntos
Algoritmos , Holografia/métodos , Humanos , Processamento de Imagem Assistida por Computador , Análise Numérica Assistida por ComputadorRESUMO
Past research has demonstrated that a digital, complex Fresnel hologram can be converted into a phase-only hologram with the use of the bi-direction error diffusion (BERD) algorithm. However, the recursive nature error diffusion process is lengthy and increases monotonically with hologram size. In this paper, we propose a method to overcome this problem. Briefly, each row of a hologram is partitioned into short non-overlapping segments, and a localized error diffusion algorithm is applied to convert the pixels in each segment into phase only values. Subsequently, the error signal is redistributed with low-pass filtering. As the operation on each segment is independent of others, the conversion process can be conducted at high speed with the graphic processing unit. The hologram obtained with the proposed method, known as the Localized Error Diffusion and Redistribution (LERDR) hologram, is over two orders of magnitude faster than that obtained by BERD for a 2048×2048 hologram, exceeding the capability of generating quality phase-only holograms in video rate.
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With the advancement of computing and optical technologies, it is now possible to capture digital holograms of real-life object scenes. Theoretically, through the analysis of a hologram, the three-dimensional (3D) objects coded on the hologram can be identified. However, being different from an optical image, a hologram is composed of complicated fringes that cannot be analyzed easily with traditional computer vision methods. Over the years, numerous important research investigations have been attempted to provide viable solutions to this problem. The aim of this work is three-fold. First, we provide a quick walkthrough on the overall development of holographic-based 3D object recognition (H3DOR) in the past five decades, from film-based approaches to digital-based innovation. Second, we describe in more detail a number of selected H3DOR methods that are introduced at different timelines, starting from the late sixties and then from the seventies, where viable digital holographic-based 3D recognition methods began to emerge. Finally, we present our work on digital holographic, pose-invariant 3D object recognition that is based on a recently introduced virtual diffraction plane framework. As our method has not been reported elsewhere, we have included some experimental results to demonstrate the feasibility of the approach.
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In this paper, a fast method for displaying a digital, real and off-axis Fresnel hologram on a lower resolution device is reported. Preserving the original resolution of the hologram upon display is one of the important attributes of the proposed method. Our method can be divided into 3 stages. First, a digital hologram representing a given three dimensional (3D) object is down-sampled based on a fix, jitter down-sampling lattice. Second, the down-sampled hologram is interpolated, through pixel duplication, into a low resolution hologram that can be displayed with a low-resolution spatial light modulator (SLM). Third, the SLM is overlaid with a grating which is generated based on the same jitter down-sampling lattice that samples the hologram. The integration of the grating and the low-resolution hologram results in, to a good approximation, the resolution of the original hologram. As such, our proposed method enables digital holograms to be displayed with lower resolution SLMs, paving the way for the development of low-cost holographic video display.
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Holografia/instrumentação , Holografia/métodos , Aumento da Imagem/instrumentação , Aumento da Imagem/métodos , Imageamento Tridimensional/instrumentação , Imageamento Tridimensional/métodos , Refratometria/instrumentação , Algoritmos , Desenho de Equipamento , Análise de Falha de Equipamento , Refratometria/métodosRESUMO
We report a novel and fast method for converting a digital, complex Fresnel hologram into a phase-only hologram. Briefly, the pixels in the complex hologram are scanned sequentially in a row by row manner. The odd and even rows are scanned from opposite directions, constituting to a bidirectional error diffusion process. The magnitude of each visited pixel is forced to be a constant value, while preserving the exact phase value. The resulting error is diffused to the neighboring pixels that have not been visited before. The resulting novel phase-only hologram is called the bidirectional error diffusion (BERD) hologram. The reconstructed image from the BERD hologram exhibits high fidelity as compared with those obtained with the original complex hologram.
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Adaptive Optical Scanning Holography (AOSH) represents a powerful technique that employs an adaptive approach to selectively omit certain lines within holograms, guided by the utilization of Normalized-Mean-Error (NME) as a predictive measure. This approach effectively diminishes scanning time and conserves the storage space required for data preservation. However, there exists alternative methods superior to NME in terms of evaluating the model's efficacy. This paper introduces two novel methods, namely Normalized-Root-Mean-Square-Error (NRMSE) and Normalized-Mean-Square-Error (NMSE), into the AOSH system, leading to the development of NRMSE-AOSH and NMSE-AOSH. These new systems aim to further minimize duration of holographic recording. Through a comparative analysis of hologram lines between the two newly proposed AOSH systems and the original AOSH, we demonstrate that both NRMSE-AOSH and NMSE-AOSH effectively reduce the number of hologram lines while maintaining the hologram's informational content. Among the three methods, our two new methods exhibit better performance compared with the original method.
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We report a low complexity, non-iterative method for enhancing the sharpness, brightness, and contrast of the pictorial content that is recorded in a digital hologram, without the need of re-generating the latter from the original object scene. In our proposed method, the hologram is first back-projected to a 2-D virtual diffraction plane (VDP) which is located at close proximity to the original object points. Next the field distribution on the VDP, which shares similar optical properties as the object scene, is enhanced. Subsequently, the processed VDP is expanded into a full hologram. We demonstrate two types of enhancement: a modified histogram equalization to improve the brightness and contrast, and localized high-boost-filtering (LHBF) to increase the sharpness. Experiment results have demonstrated that our proposed method is capable of enhancing a 2048x2048 hologram at a rate of around 100 frames per second. To the best of our knowledge, this is the first time real-time image enhancement is considered in the context of digital holography.
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Artefatos , Holografia/instrumentação , Aumento da Imagem/instrumentação , Refratometria/instrumentação , Processamento de Sinais Assistido por Computador/instrumentação , Gravação em Vídeo/instrumentação , Desenho Assistido por Computador , Desenho de Equipamento , Análise de Falha de Equipamento , Luz , Espalhamento de RadiaçãoRESUMO
Relighting is an important technique in photography which enables the optical properties of a picture to be modified without retaking it again. However, different from an optical image, a digital hologram cannot be relit by simply varying the value of individual pixel, as each of them is representing holistic information of the entire object scene. In this paper, we propose a fast method for the relighting of a digital hologram. First, the latter is projected to a virtual wavefront recording plane (WRP) that is located close to the object scene. Next, the WRP is relit, and subsequently expanded into a full hologram. Experiment results have demonstrated that our proposed method is capable of relighting a 2048x2048 hologram at a rate of over 50 frames per second. To the best of our knowledge, this is the first time relighting is considered in the context of holography.
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Algoritmos , Holografia/métodos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Iluminação/métodos , Processamento de Sinais Assistido por Computador , Sistemas Computacionais , Aumento da Imagem/métodos , Reprodutibilidade dos Testes , Sensibilidade e EspecificidadeRESUMO
We report, for the first time, the concept and generation of a novel Fresnel hologram called the digital binary mask programmable hologram (BMPH). A BMPH is comprised of a static, high resolution binary grating that is overlaid with a lower resolution binary mask. The reconstructed image of the BMPH can be programmed to approximate a target image (including both intensity and depth information) by configuring the pattern of the binary mask with a simple genetic algorithm (SGA). As the low resolution binary mask can be realized with less stringent display technology, our method enables the development of simple and economical holographic video display.
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Algoritmos , Holografia/instrumentação , Aumento da Imagem/métodos , Lasers , Processamento de Sinais Assistido por Computador/instrumentação , Desenho Assistido por Computador , Desenho de Equipamento , Humanos , IluminaçãoRESUMO
Past research has demonstrated that a three-dimensional object scene can be converted into a digital hologram. Subsequently, the object scene can be reconstructed from the hologram with an iterative blind sectional image reconstruction (BSIR) method. However, the computation is extremely intensive, and escalated with the size of holograms. To overcome this problem, we propose a fast BSIR method that reconstructs sectional images with less out-of-focus haze. While the technique proposed here is applicable in general to holography for sectioning, we use holograms acquired by optical scanning holography as examples to show the method's effectiveness.
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In the past two decades, generation and encryption of holographic images have been identified as two important areas of investigation in digital holography. The integration of these two technologies has enabled images to be encrypted with more dimensions of freedom on top of simply employing the encryption keys. Despite the moderate success attained to date, and the rapid advancement of computing technology in recent years, the heavy computation load involved in these two processes remains a major bottleneck in the evolution of the digital holography technology. To alleviate this problem, we have proposed a fast and economical solution which is capable of generating, and at the same time encrypting, holograms with numerical means. In our method, the hologram formation mechanism is decomposed into a pair of one-dimensional (1D) processes. In the first stage, a given three-dimensional (3D) scene is partitioned into a stack of uniformed spaced horizontal planes and converted into a set of hologram sublines. Next, the sublines are expanded to a hologram by convolving it with a 1D reference signal. To encrypt the hologram, the reference signal is first convolved with a key function in the form of a maximum length sequence (also known as MLS, or M-sequence). The use of a MLS has two advantages. First, an MLS is spectrally flat so that it will not jeopardize the frequency spectrum of the hologram. Second, the autocorrelation function of an MLS is close to a train of Kronecker delta function. As a result, the encrypted hologram can be decoded by correlating it with the same key that is adopted in the encoding process. Experimental results reveal that the proposed method can be applied to generate and encrypt holograms with a small number of computations. In addition, the encrypted hologram can be decoded and reconstructed to the original 3D scene with good fidelity.
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Optical Scanning Holography (OSH) is a powerful technique that employs a single-pixel sensor and a row-by-row scanning mechanism to capture the hologram of a wide-view, three-dimensional object. However, the time required to acquire a hologram with OSH is rather lengthy. In this paper, we propose an enhanced framework, which is referred to as Adaptive OSH (AOSH), to shorten the holographic recording process. We have demonstrated that the AOSH method is capable of decreasing the acquisition time by up to an order of magnitude, while preserving the content of the hologram favorably.
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In this paper we report a low complexity compression method that is suitable for compact optical scanning holography (OSH) systems with different optical settings. Our proposed method can be divided into 2 major parts. First, an automatic decision maker is applied to select the rows of holographic pixels to be scanned. This process enhances the speed of acquiring a hologram, and also lowers the data rate. Second, each row of down-sampled pixels is converted into a one-bit representation with delta modulation (DM). Existing DM-based hologram compression techniques suffers from the disadvantage that a core parameter, commonly known as the step size, has to be determined in advance. However, the correct value of the step size for compressing each row of hologram is dependent on the dynamic range of the pixels, which could deviate significantly with the object scene, as well as OSH systems with different opical settings. We have overcome this problem by incorporating a dynamic step-size adjustment scheme. The proposed method is applied in the compression of holograms that are acquired with 2 different OSH systems, demonstrating a compression ratio of over two orders of magnitude, while preserving favorable fidelity on the reconstructed images.