Displays最新文献_第6页

A comparative analysis of machine learning methods for display characterization 用于显示特征的机器学习方法比较分析

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-10-09 DOI: 10.1016/j.displa.2024.102849

Khleef Almutairi , Samuel Morillas , Pedro Latorre-Carmona , Makan Dansoko , María José Gacto

This paper explores the application of various machine-learning methods for characterizing displays of technologies LCD, OLED, and QLED to achieve accurate color reproduction. These models are formed from input (device-dependent RGB data) and output (device-independent XYZ coordinates) data obtained from three different displays. Training and test datasets are built using

R G B

data measured directly from the displays and corresponding

X Y Z

coordinates measured with a high-precision colorimeter. A key aspect of this research is the application fuzzy inference systems for building interpretable models. These models offer the advantage of not only achieving good performance in color reproduction, but also providing physical insights into the relationships between the

R G B

inputs and the resulting

X Y Z

outputs. This interpretability allows for a deeper understanding of the display’s behavior. Furthermore, we compare the performance of fuzzy models with other popular machine-learning approaches, including those based on neural networks and decision trees. By evaluating the strengths and weaknesses of each method, we aim to identify the most effective approach for display characterization. The effectiveness of each method is assessed by its ability to accurately reproduce and display colors, as measured by the

Δ E_{00}

visual error metric. Our findings indicate that the Fuzzy Modeling and Identification (FMID) method is particularly effective, allowing for an optimal balance between high accuracy and interpretability. Its competitive performance across all display types, combined with its valuable interpretability, provides insights for potential future calibration and optimization strategies. The results will shed light on whether machine learning methods offer an advantage over traditional physical models, particularly in scenarios with limited data. Additionally, the study will contribute to the understanding of the interpretability benefits offered by fuzzy inference systems in the context of LCD display characterization.

本文探讨了各种机器学习方法在表征 LCD、OLED 和 QLED 技术显示屏方面的应用，以实现准确的色彩再现。这些模型由三种不同显示器的输入（与设备相关的 RGB 数据）和输出（与设备无关的 XYZ 坐标）数据组成。训练和测试数据集是使用直接从显示器测量的 RGB 数据和使用高精度色度计测量的相应 XYZ 坐标建立的。这项研究的一个重要方面是应用模糊推理系统建立可解释的模型。这些模型的优势在于不仅能实现良好的色彩还原性能，还能提供有关 RGB 输入和 XYZ 输出结果之间关系的物理洞察力。这种可解释性有助于加深对显示器行为的理解。此外，我们还将模糊模型的性能与其他流行的机器学习方法（包括基于神经网络和决策树的方法）进行了比较。通过评估每种方法的优缺点，我们旨在找出最有效的显示表征方法。每种方法的有效性都是通过其准确再现和显示色彩的能力来评估的，并用 ΔE00 视觉误差指标来衡量。我们的研究结果表明，模糊建模和识别 (FMID) 方法特别有效，能够在高精度和可解释性之间实现最佳平衡。在所有显示类型中，该方法的性能都很有竞争力，再加上其宝贵的可解释性，为未来潜在的校准和优化策略提供了启示。研究结果将揭示机器学习方法是否比传统物理模型更具优势，尤其是在数据有限的情况下。此外，这项研究还将有助于人们了解模糊推理系统在液晶显示屏表征方面提供的可解释性优势。

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引用次数: 0

TRRHA: A two-stream re-parameterized refocusing hybrid attention network for synthesized view quality enhancement TRRHA：用于提高合成视图质量的双流重参数再聚焦混合注意力网络

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-10-09 DOI: 10.1016/j.displa.2024.102843

Ziyi Cao , Tiansong Li , Guofen Wang , Haibing Yin , Hongkui Wang , Li Yu

In multi-view video systems, the decoded texture video and its corresponding depth video are utilized to synthesize virtual views from different perspectives using the depth-image-based rendering (DIBR) technology in 3D-high efficiency video coding (3D-HEVC). However, the distortion of the compressed multi-view video and the disocclusion problem in DIBR can easily cause obvious holes and cracks in the synthesized views, degrading the visual quality of the synthesized views. To address this problem, a novel two-stream re-parameterized refocusing hybrid attention (TRRHA) network is proposed to significantly improve the quality of synthesized views. Firstly, a global multi-scale residual information stream is applied to extract the global context information by using refocusing attention module (RAM), and the RAM can detect the contextual feature and adaptively learn channel and spatial attention feature to selectively focus on different areas. Secondly, a local feature pyramid attention information stream is used to fully capture complex local texture details by using re-parameterized refocusing attention module (RRAM). The RRAM can effectively capture multi-scale texture details with different receptive fields, and adaptively adjust channel and spatial weights to adapt to information transformation at different sizes and levels. Finally, an efficient feature fusion module is proposed to effectively fuse the extracted global and local information streams. Extensive experimental results show that the proposed TRRHA achieves significantly better performance than the state-of-the-art methods. The source code will be available at https://github.com/647-bei/TRRHA.

在多视角视频系统中，利用三维高效视频编码（3D-HEVC）中基于深度图像的渲染（DIBR）技术，将解码后的纹理视频及其对应的深度视频合成为不同视角的虚拟视图。然而，压缩多视角视频的失真和 DIBR 中的不确定性问题容易导致合成视图出现明显的孔洞和裂缝，降低合成视图的视觉质量。针对这一问题，我们提出了一种新型的双流重参数再聚焦混合注意力（TRRHA）网络，以显著提高合成视图的质量。首先，全局多尺度残留信息流通过重新聚焦注意力模块（RAM）提取全局上下文信息，RAM 可以检测上下文特征，并自适应地学习通道和空间注意力特征，从而选择性地聚焦于不同区域。其次，利用重新参数化的重新聚焦注意力模块（RRAM），使用局部特征金字塔注意力信息流来充分捕捉复杂的局部纹理细节。RRAM 能有效捕捉具有不同感受野的多尺度纹理细节，并能自适应地调整通道和空间权重，以适应不同大小和层次的信息转换。最后，还提出了一个高效的特征融合模块，以有效融合提取的全局和局部信息流。广泛的实验结果表明，所提出的 TRRHA 性能明显优于最先进的方法。源代码可在 https://github.com/647-bei/TRRHA 上获取。

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引用次数: 0

Seasickness and partial peripheral vision obstruction with versus without an artificial horizon 晕船和部分周边视力受阻，有无人工地平线之分

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-10-05 DOI: 10.1016/j.displa.2024.102851

Camille de Thierry de Faletans, Maxime Misericordia, Jean-Marc Vallier, Pascale Duché, Eric Watelain

Motion sickness (MS) is common when subjects are exposed to unfamiliar motion and affect individuals during travel. This study examines the immediate effect of two visual devices, in the form of glasses, on MS symptoms and associated physiological effects. The hypothesis is that peripheral vision obstruction reduces MS and that an additional beneficial effect could be observed when it is combined with an artificial horizon. Fifteen subjects with moderate to severe susceptibility to MS were exposed to a boat simulator in three conditions. Symptoms were assessed immediately after exposure. Time spent in the simulator, heart rate, and temperature were also recorded. The intensity of symptoms at the end of the experience did not differ, but time spent in the simulator before the onset of symptoms was significantly longer with peripheral vision obstruction (+36 %) and with both techniques combined (+40 %) than in the control condition. No difference was observed between the combined condition and peripheral vision obstruction alone. The glasses device used in this study (with or without an artificial horizon) delays the onset of symptoms. Further research is needed to confirm the mechanism that explains the benefits and to evaluate these effects during prolonged exposure to MS-inducing stimuli or after a period of familiarization with the device.

晕动病（MS）是一种常见病，当受试者在旅行过程中接触到陌生的运动并对其产生影响时，就会出现这种症状。本研究探讨了两种眼镜形式的视觉设备对 MS 症状和相关生理效应的直接影响。研究假设外周视力障碍可减轻多发性硬化症的症状，当外周视力障碍与人工地平线相结合时，可观察到额外的有益效果。15 名患有中度至重度多发性硬化症的受试者在三种条件下接触了模拟船。暴露后立即对症状进行评估。在模拟器中停留的时间、心率和体温也被记录下来。体验结束时的症状强度没有差异，但在周边视觉受阻（+36%）和两种技术相结合（+40%）的情况下，症状出现前在模拟器中度过的时间明显长于对照组。两种方法结合使用时与单独使用周边视觉受阻时没有差异。本研究中使用的眼镜装置（无论有无人工视平线）都会延迟症状的出现。还需要进一步研究，以确认产生这种益处的机制，并在长时间暴露于诱发多发性硬化症的刺激下或在熟悉该装置一段时间后对这些效果进行评估。

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引用次数: 0

Ultrathin metasurface for super multi-view 3D display with linear and circular polarization control 用于超级多视角 3D 显示器的超薄元表面，具有线性和圆偏振控制功能

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-10-02 DOI: 10.1016/j.displa.2024.102848

Munzza Ahmad, Jingnan Li, Haowen Ma, Juan Liu

Multiview 3D display technologies are advantageous due to their smooth motion parallax, visual discomfort alleviation, and wide depth of focus. However, the potential applications of this technology are constrained by its bulky size and limited light modulation capability. Metasurfaces offer diverse wavefront control by manipulating the phase, amplitude, and polarization of light. They provide design freedom and high image quality for multiview 3D display technologies. Here, we propose an ultrathin metasurface-based super multiview 3D display that can effectively modulate the flexibility of linearly polarized (LP) and circularly polarized (CP) electromagnetic waves. Numerical results demonstrate that it can produce 24 views together for LP and CP waves and high-quality reconstructed 3D images are obtained. The suggested metasurface for super multiview 3D display is promising to underpin the advancement of meta-optics-based operations in 3D display, imaging and integrated optics.

多视角 3D 显示技术具有平滑的运动视差、减轻视觉不适和宽广的焦距等优点。然而，由于其体积庞大，光调制能力有限，这项技术的潜在应用受到了限制。元表面可通过操纵光的相位、振幅和偏振来提供多样化的波前控制。它们为多视角 3D 显示技术提供了设计自由度和高图像质量。在此，我们提出了一种基于超薄元表面的超级多视角三维显示屏，它能有效调节线性偏振（LP）和圆偏振（CP）电磁波的柔性。数值结果表明，它可以同时生成 LP 波和 CP 波的 24 个视图，并获得高质量的重建三维图像。建议用于超级多视图三维显示的元表面有望为三维显示、成像和集成光学中基于元光学的操作提供支持。

引用次数: 0

Novel intelligent defects detection of boiler water walls in thermal power plants based on OFM_SSD 基于 OFM_SSD 的火力发电厂锅炉水墙新型智能缺陷检测

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-30 DOI: 10.1016/j.displa.2024.102847

Yongming Han , Lei Wang , Jintao Liu , Liang Yuan , Hongxu Liu , Bo Ma , Zhiqiang Geng

The boiler is a critical component of conventional thermal power systems, where surface flaws in boiler water walls can significantly compromise safety and availability, potentially leading to substantial loss of life and property. Traditional detection methods, whether manual or based on machine learning, often prove costly, inefficient and time-consuming, failing to meet the stringent requirements for water wall inspection. Therefore, a novel surface defect detection model integrating an improved single shot multibox detector (SSD) with the optical flow method (OFM) (OFM_SSD) is proposed. The OFM enhances data sample diversity by augmenting the dataset derived from thermal power plants, while the incorporation of deconvolution techniques improves the model receptive field, thereby enhancing its ability to detect and classify small defects. Comprehensive experiments demonstrate that the OFM_SSD outperforms several existing models including the SSD model based on traditional expanded datasets (T_SSD), you only look once (YOLO), ordinary SSD, Regions with the CNN(R_CNN), and Deconvolution-only SSD (DSSD) in terms of accuracy in defect localization and classification. This advancement of the OFM_SSD not only reduces operational costs but also enhances detection capabilities, ultimately contributing to safer and more efficient operations within thermal power plants.

锅炉是传统火力发电系统的重要组成部分，锅炉水墙的表面缺陷会严重影响其安全性和可用性，并可能导致重大的生命和财产损失。传统的检测方法，无论是人工检测还是基于机器学习的检测，往往都被证明成本高、效率低、耗时长，无法满足水墙检测的严格要求。因此，我们提出了一种新型表面缺陷检测模型，它将改进的单发多箱检测器（SSD）与光流方法（OFM）（OFM_SSD）集成在一起。OFM 通过增强来自火力发电厂的数据集来提高数据样本的多样性，而去卷积技术的融入则改善了模型的感受野，从而提高了其检测和分类小缺陷的能力。综合实验证明，OFM_SSD 在缺陷定位和分类的准确性方面优于现有的几种模型，包括基于传统扩展数据集的 SSD 模型（T_SSD）、只看一次（YOLO）、普通 SSD、带 CNN 的区域（R_CNN）和去卷积 SSD（DSSD）。OFM_SSD 的这一进步不仅降低了运营成本，还增强了检测能力，最终有助于火力发电厂更安全、更高效地运营。

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引用次数: 0

A multi-frame fusion video deraining neural network based on depth and luminance features 基于深度和亮度特征的多帧融合视频派生神经网络

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-30 DOI: 10.1016/j.displa.2024.102842

Fengqi Li , Mengchao Guo , Rui Su , Yanjuan Wang , Yi Wang , Fengqiang Xu

Rainy weather is a common natural occurrence, but capturing clear and accurate images in rainy conditions can be challenging. Consequently, addressing the effects of rain on video imagery is essential for enhancing visual quality and the accuracy and reliability of computer vision applications. In this work, we introduce a novel rain model accompanied by a multi-frame fusion video rain removal algorithm that exploits depth and luminance features. We present an innovative three-stage video deraining methodology that synergizes multi-frame fusion with advanced neural network design to achieve highly realistic and clear rain removal. Our Option-Flow-Depth-Luminance (OFDL) Derain algorithm propels the research forward by offering a new perspective on rain removal. Incorporating depth and luminance features into image processing, we devise a novel rain model that allows the algorithm to handle complex environments and a variety of rain patterns effectively. Additionally, our model takes into account degradation factors such as rain streaks, accumulation, runoff, and occlusion, leading to the generation of more authentic rain-affected images that improve the training and performance evaluation of the model. Experimental tests conducted on the RainSynLight25, RainSynComplex25, and NTURain datasets demonstrate that our method outperforms current state-of-the-art techniques, achieving increases of 4.3 dB, 2.2 dB, and 2.2 dB in PSNR, and enhancements of 0.062, 0.109, and 0.008 in Structural Similarity Index Measure (SSIM), respectively. Moreover, our approach exhibits superior processing speed, further underscoring its practical advantages.

雨天是一种常见的自然现象，但在雨天条件下捕捉清晰、准确的图像却极具挑战性。因此，解决雨水对视频图像的影响对于提高视觉质量以及计算机视觉应用的准确性和可靠性至关重要。在这项工作中，我们介绍了一种新颖的雨水模型，以及一种利用深度和亮度特征的多帧融合视频雨水去除算法。我们提出了一种创新的三阶段视频除雨方法，该方法将多帧融合与先进的神经网络设计相结合，实现了高度逼真和清晰的除雨效果。我们的 "选项-流量-深度-亮度"（OFDL）去噪算法为去噪提供了一个全新的视角，推动了研究的发展。我们将深度和亮度特征融入图像处理，设计出一种新颖的雨模型，使算法能够有效处理复杂环境和各种雨模式。此外，我们的模型还考虑到了雨水条纹、积聚、径流和遮挡等退化因素，从而生成了更真实的雨水影响图像，改进了模型的训练和性能评估。在 RainSynLight25、RainSynComplex25 和 NTURain 数据集上进行的实验测试表明，我们的方法优于目前最先进的技术，在 PSNR 方面分别提高了 4.3 dB、2.2 dB 和 2.2 dB，在结构相似性指数（SSIM）方面分别提高了 0.062、0.109 和 0.008。此外，我们的方法还显示出卓越的处理速度，进一步凸显了其实用优势。

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引用次数: 0

Knowledge graph of agricultural engineering technology based on large language model 基于大语言模型的农业工程技术知识图谱

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-26 DOI: 10.1016/j.displa.2024.102820

Haowen Wang, Ruixue Zhao

Agriculture is an industry that has evolved alongside human evolution and has faithfully fulfilled its core mission of food supply. With the reduction of rural labor, the progress of artificial intelligence and the development of Internet of Things technology, it is hoped that the efficiency and productivity of the agricultural industry can be improved. Recently, with the development of information and intelligent technology, agricultural production and management have been significantly enhanced. However, there is still a considerable challenge in effectively integrating the vast amount of fragmented information for downstream applications. An agricultural knowledge graph (AGKG) will serve as the foundation for achieving these goals. Knowledge graphs can be general or domain-specific, and are the basis for many applications, such as search engines, online question-and-answer services, and knowledge inference. Therefore, there are many knowledge graphs, including Wikidata and DBpedia, for accessing structured knowledge. Although some general knowledge graphs contain some entities and relationships related to agriculture, there are no domain-specific knowledge graphs specifically for agricultural applications. Therefore, this paper proposes an agricultural knowledge graph (AGKG) for automatically integrating large amounts of agricultural data from the Internet. By applying natural language processing and deep learning technologies, AGKG can automatically identify agricultural entities from unstructured text and connect them to form a knowledge graph. In addition, we have described the typical scenarios of our AGKG and validated it through real-world applications such as agricultural entity retrieval and agricultural question-answering.

农业是伴随人类进化而发展的产业，忠实地履行着粮食供应的核心使命。随着农村劳动力的减少、人工智能的进步和物联网技术的发展，农业产业的效率和生产力有望得到提高。近来，随着信息和智能技术的发展，农业生产和管理水平显著提高。然而，如何将大量零散的信息有效地整合到下游应用中，仍然是一个相当大的挑战。农业知识图谱（AGKG）将成为实现这些目标的基础。知识图谱可以是通用的，也可以是特定领域的，是搜索引擎、在线问答服务和知识推理等许多应用的基础。因此，有许多知识图谱，包括 Wikidata 和 DBpedia，用于访问结构化知识。虽然一些通用知识图谱包含一些与农业相关的实体和关系，但还没有专门针对农业应用的特定领域知识图谱。因此，本文提出了一种农业知识图谱（AGKG），用于自动整合互联网上的大量农业数据。通过应用自然语言处理和深度学习技术，AGKG 可以从非结构化文本中自动识别农业实体，并将它们连接起来形成知识图谱。此外，我们还介绍了 AGKG 的典型应用场景，并通过农业实体检索和农业问题解答等实际应用对其进行了验证。

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引用次数: 0

Size and temperature effects on optoelectronic properties of Micro-LED arrays for display applications 尺寸和温度对用于显示应用的微型 LED 阵列光电特性的影响

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-19 DOI: 10.1016/j.displa.2024.102841

Yijian Zhou , Tianxi Yang , Jin Li , Yuchen Lu , Yang Li , Qiwei Li , Caihong Yan , Shuaishuai Wang , Jie Sun , Qun Yan

In recent years, Micro-light-emitting diode (Micro-LED) has attracted much attention in the display field, because it provides the possibility of high pixel density, etc. The implementation of high pixel density is accompanied by the reduction of size, during which the performance degradation caused by sidewall defects gradually increases. At the same time, the increase in power density and difficulty in heat dissipation caused by high pixel density can also lead to poor thermal management, resulting in an increase in junction temperature, thus affecting the display effect. In this paper, we prepared seven different sizes of Micro-LED and studied the influence of size and temperature effects on the optoelectronic properties. Smaller-sized Micro-LED could withstand higher current densities because it was not affected by the current crowding effect. However, it tends to have a larger series resistance (R_S) and a lower external quantum efficiency (EQE) due to sidewall defects created during etching. The luminance of the 100 μm and 7 μm Micro-LED was 340000 cd/m² (at 83 A/cm²) and 32000 cd/m² (at 773 A/cm²), respectively. The peak EQE of 100 μm Micro-LED was 16.87 %. On this basis, the temperature-dependence of the optoelectronic properties of 10 μm and 50 μm Micro-LED were studied. The larger the size of Micro-LED, the better the operational stability it exhibited. From the room temperature (RT) rose to 100 ℃, the EQE of the 10 μm and 50 μm Micro-LED decreased by 16 % and 13.1 %, respectively. These experimental results provide important data for the design and preparation of Micro-LED of different sizes and for exploring the operational stability at high temperatures.

近年来，微型发光二极管（Micro-LED）在显示领域备受关注，因为它提供了高像素密度等可能性。高像素密度的实现伴随着尺寸的缩小，而在缩小的过程中，侧壁缺陷导致的性能下降也逐渐增加。同时，高像素密度带来的功率密度增加和散热困难也会导致热管理不善，造成结温升高，从而影响显示效果。本文制备了七种不同尺寸的 Micro-LED，并研究了尺寸和温度效应对其光电特性的影响。由于不受电流拥挤效应的影响，较小尺寸的 Micro-LED 可以承受较高的电流密度。然而，由于蚀刻过程中产生的侧壁缺陷，它往往具有较大的串联电阻（RS）和较低的外部量子效率（EQE）。100 μm 和 7 μm Micro-LED 的亮度分别为 340000 cd/m2（83 A/cm2 时）和 32000 cd/m2（773 A/cm2 时）。100 μm Micro-LED 的峰值 EQE 为 16.87%。在此基础上，研究了 10 μm 和 50 μm Micro-LED 光电特性的温度依赖性。Micro-LED 的尺寸越大，其工作稳定性越好。从室温（RT）上升到 100 ℃，10 μm 和 50 μm Micro-LED 的 EQE 分别下降了 16 % 和 13.1 %。这些实验结果为设计和制备不同尺寸的 Micro-LED 以及探索高温下的工作稳定性提供了重要数据。

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引用次数: 0

MSI-DTrans: A multi-focus image fusion using multilayer semantic interaction and dynamic transformer MSI-DTrans：利用多层语义交互和动态变换器进行多焦点图像融合

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-17 DOI: 10.1016/j.displa.2024.102837

Hao Zhai, Yuncan Ouyang, Nannan Luo, Lianhua Chen, Zhi Zeng

Multi-focus image fusion (MFIF) aims to utilize multiple images with different focal lengths to fuse into a single full-focus image. This process enhances the realism and clarity of the resulting image. In this paper, a MFIF method called MSI-DTrans was proposed. On the one hand, in order to fully utilize all the effective information that the source image carries, the proposed method adopts a multilayer semantic interaction strategy to enhance the interaction of high-frequency and low-frequency information. This approach gradually mines more abstract semantic information, guiding the generation of feature maps from coarse to fine. On the other hand, a parallel multi-scale joint self-attention computation model is designed. The model adopts dynamic sense field and dynamic token embedding to overcome the performance degradation problem when dealing with multi-scale objects. This enables self-attention to integrate long-range dependencies between objects of different scales and reduces computational overhead. Numerous experimental results show that the proposed method effectively avoids image distortion, achieves better visualization results, and demonstrates good competitiveness with many state-of-the-art methods in terms of qualitative and quantitative analysis, as well as efficiency comparison. The source code is available at https://github.com/ouyangbaicai/MSI-DTrans.

多焦图像融合（MFIF）旨在利用不同焦距的多幅图像融合成一幅全焦图像。这一过程可增强图像的真实感和清晰度。本文提出了一种名为 MSI-DTrans 的 MFIF 方法。一方面，为了充分利用源图像所携带的所有有效信息，所提出的方法采用了多层语义交互策略，以增强高频和低频信息的交互。这种方法能逐渐挖掘出更多抽象的语义信息，引导特征图的生成由粗到细。另一方面，设计了一个并行的多尺度联合自我注意计算模型。该模型采用动态感知场和动态标记嵌入来克服处理多尺度对象时的性能下降问题。这使得自注意能够整合不同尺度对象之间的长距离依赖关系，并减少计算开销。大量实验结果表明，所提出的方法有效地避免了图像失真，实现了更好的可视化效果，并在定性和定量分析以及效率比较方面与许多最先进的方法相比具有良好的竞争力。源代码见 https://github.com/ouyangbaicai/MSI-DTrans。

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引用次数: 0

Ultra-wide viewing angle holographic display system based on spherical diffraction 基于球面衍射的超宽视角全息显示系统

IF 3.7 2区工程技术 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Displays

Pub Date : 2024-09-17 DOI: 10.1016/j.displa.2024.102839

Jun Wang , Mohan Wang , Yang Wu , Jie Zhou , Chun Chen , Di Wang , Qiong-Hua Wang

In the field of holographic displays, achieving a large viewing angle (LVA) has long been an essential and formidable challenge due to the limited diffraction angle of planar spatial light modulators (SLMs). Spherical holography, which allows observation from all perspectives, represents a practical approach to achieve the LVA. However, the physical limitations of commercial SLMs constrain direct implementation, making the realization of spherical holographic displays almost impractical and thus hindering technological advancement. This paper introduces an optical solution for spherical holographic display system, enabling the accurate reproduction of ultra-wide viewing angles and large objects. Our system utilizes a novel technique involving a convex parabolic mirror to convert an incident plane wave into a spherical wave. This innovative strategy permits the use of a planar SLM to create a 360°spherical holographic display. Additionally, we address the sampling issue for generating spherical holograms by constraining the point spread function (PSF), reducing the number of samples, and adapting it for visible light. Numerical simulations and optical experiments validate our success in achieving an ultra-wide viewing angle with a 360°horizontal angle and an 80°zenith angle range. Our system outperforms the state-of-the-art holographic-optical-elements approach both in computation speed and object size. We believe that our work significantly advances spherical holographic displays and offers a practical solution with vast potential applications in medicine, geology, and astronomy.

在全息显示领域，由于平面空间光调制器（SLM）的衍射角有限，实现大视角（LVA）一直是一项艰巨的基本挑战。球面全息技术允许从所有角度进行观察，是实现大视角显示的一种实用方法。然而，商用空间光调制器的物理限制制约了其直接实施，使得球形全息显示的实现几乎不切实际，从而阻碍了技术进步。本文介绍了一种球形全息显示系统的光学解决方案，可精确再现超宽视角和大型物体。我们的系统采用了一种新技术，利用凸抛物面镜将入射平面波转换为球面波。这种创新策略允许使用平面 SLM 来创建 360° 球形全息显示。此外，我们还通过限制点扩散函数 (PSF)、减少样本数量并使其适用于可见光，解决了生成球形全息图的采样问题。数值模拟和光学实验验证了我们成功实现了 360° 水平角和 80° 天顶角范围的超宽视角。我们的系统在计算速度和物体尺寸方面都优于最先进的全息-光学元件方法。我们相信，我们的工作极大地推动了球形全息显示技术的发展，并提供了一种实用的解决方案，在医学、地质学和天文学领域具有广阔的应用前景。

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引用次数: 0