- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Measurement and Investigation of the Incident Radiation in Case of Using Transparent Pyramidal Covers for Improving the Solar Panel’s Power Output
摘要： A new approach is presented to enhance the solar radiation intensity incident over the solar panel by using a transparent cover of pyramidal shapes. The pyramidal cover shape is manufactured of Polymethylmethacrylate dielectric material. The normal height of each pyramid is considered as a ratio of the base length. This ratio is considered in the present study to be 0.5, 1, and 1.5. The effect of the pyramidal covers on the solar panel voltage has been studied at different conditions. The experimental results confirm that the pyramidal cover shape causes the improvement to the solar panel output voltage by 4.2% when covering all the panel with pyramids of R=1 with a light incidence angle of 90 when the light rays come parallel to the panel surface. This improvement is found to decreases with covering fewer areas of the solar panel and with fewer incidence angles. It is found also that the distance between the light source and the panel is proportional to the output voltage improvement ratio compared to the panels output voltage without pyramidal cover. A mathematical model has been presented to prove the concept of increasing the electric and magnetic field of the incident radiation from the sun in case of presence of the transverse transparent barrier. Moreover, a mathematical ray tracking model was presented and validated with the experimental results by a maximum relative error of 14.8%
关键词： solar panel improvement,Incident radiation,enhancement of light field radiation,polarization,enhancement of solar radiation,transverse of transparent barrier
更新于2025-09-23 15:23:52
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - High-Quality Virtual View Synthesis for Light Field Cameras Using Multi-Loss Convolutional Neural Networks
摘要： Although light field cameras record both spatial and angular information, their angular and spatial resolutions are limited when capturing light field data. Thus, it is required to synthesize virtual views. In this paper, we propose high-quality virtual view synthesis based on multi-loss convolutional neural networks (CNN). We adopt multi-loss function for view synthesis in both pixel and feature spaces to increase the angular resolution of light field data. We combine three losses of feature loss, edge loss, and mean squared error (MSE) loss into the multi-loss function. We learn the view synthesis function based on simple three layers of CNN. Experimental results show that the proposed method successfully produces virtual views from light field data and outperforms state-of-the-arts in terms of peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM).
关键词： Convolutional neural networks,loss function,virtual view synthesis,multi-loss,light field
更新于2025-09-23 15:23:52
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A multi-order derivative feature-based quality assessment model for light field image
摘要： This paper presents an image quality assessment (IQA) model exploring the multi-order derivative feature, called Multi-order Derivative Feature-based Model (MDFM), for evaluating the perceptual quality of light field image (LFI). In our approach, for the input reference and distorted LFIs, the multi-order derivative features are extracted by using the discrete derivative filter to represent the image details in different degrees. Then, the similarities of the extracted derivative features are measured independently. Finally, the weight map is established through the maximum value of the second-order derivative feature of reference and distorted LFIs, which is further utilized to pool the similarity map for generating the final score. Extensive simulation results have demonstrated that the proposed MDFM is more consistent with the perception of the HVS on the evaluation of LFI than the classical and state-of-the-art IQA methods.
关键词： Multi-order derivative feature,Light field image,Image quality assessment
更新于2025-09-23 15:23:52
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Scale and Orientation Aware EPI-Patch Learning for Light Field Depth Estimation
摘要： Epipolar Plane Image (EPI) implies some important depth cues for light field depth estimation. Intuitively, the EPI patches with different spatial scales and orientations may exhibit different features and result in different estimation precision. In this paper, we discuss this issue and present a scale and orientation aware EPI-Patch learning model for depth estimation. We take the multi-orientation EPI patches of each pixel as input, and design two types of network structures for adaptive scale selection and orientation fusion. One type is a scale-aware structure, which feeds one orientation patch into a multi-layer feed-forward network with long and short skip connections. The other type is a shared-weight network for fusing the multi-orientation features. We demonstrate the effectiveness of our model by experiments on 4D Light Field Benchmark.
关键词： scale-aware,orientation-aware,depth estimation,deep learning,EPI,light field
更新于2025-09-23 15:23:52
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Research on feature point extraction and matching machine learning method based on light field imaging
摘要： At present, there are many methods to realize the matching of specified images with features, and the basic components include image feature point detection, feature description, and image matching. Based on this background, this article has done different research and exploration around these three aspects. The image feature point detection method is firstly studied, which commonly include image edge information-based feature detection method, corner information-based detection method, and various interest operators. However, all of the traditional detection methods are involved in problems of large computation burden and time consumption. In order to solve this problem, a feature detection method based on image grayscale information-FAST operator is used in this paper, which is combined with decision tree theory to effectively improve the speed of extracting image feature points. Then, the feature point description method BRIEF operator is studied, which is a local expression of detected image feature points based on descriptors. Since the descriptor does not have rotation invariance, the detection operator is endowed by a direction that is proposed in this paper, and then the local feature description is conducted on the feature descriptor to generate a binary string array containing direction information. Finally, the feature matching machine learning method is analyzed, and the nearest search method is used to find the nearest feature point pair in Euclidean distance, of which the calculation burden is small. The simulation results show that the proposed nearest neighbor search and matching machine learning algorithm has higher matching accuracy and faster calculation speed compared with the classical feature matching algorithm, which has great advantages in processing a large number of array images captured by the light field camera.
关键词： Nearest neighbor search,Light field imaging,Image matching,Machine learning
更新于2025-09-23 15:23:52
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Virtual Image Points Based Geometrical Parameters’ Calibration for Focused Light Field Camera
摘要： In the light field imaging, the geometrical parameters' calibration of the light field camera is the foundation of computational imaging techniques, such as the calibration of the light field data, digital refocusing, depth reconstruction, all-in-focus imaging, and so on. In this paper, we propose a virtual image points based geometrical parameters' calibration for focused light field camera. In the forward model, the mapping from the object points to the virtual image points with respect to the main lens as well as the mapping from the virtual image points to the image points on the detector with respect to the microlens array are established. While calibrating geometrical parameters, the inverse problem of calculating the virtual image points from the corner on the detector is established and the model of calculating the geometrical parameters of the focused light field camera is established. Levenberg–Marquardt algorithm is used to solve the geometrical parameters iteratively. We use the checkerboard for the calibration experiment and validate the calculation via the reprojection of the checkerboard corners.
关键词： computational imaging,virtual image point,light field camera,Camera calibration
更新于2025-09-23 15:23:52
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Three-dimensional digital image correlation method based on a light field camera
摘要： With the recent development of computer vision and photographic technology, many three-dimensional (3D) modelling methods have emerged. This paper introduces a new method that combines digital image correlation (DIC) with a light field camera to reconstruct the surface of an object. Before experimentation, the surface of the object was sprayed with a speckle pattern. The parameters of the light field camera, such as the micro-lens, focus, and lens distortion, were pre-calibrated. During the experiments, raw images of the samples were recorded by a light field camera, then each was extracted to two sub-aperture images. Using the digital image correlation method, feature point matching of the corresponding sub-images was executed and the 3D space coordinates of all of the matching points were calculated using the binocular vision principle with surface topography information. The experimental results demonstrate that the method can realise 3D reshape and 3D deformation measurements using a single camera. The system has the advantage of a simple structure, large depth of field, and wide measurement range for out-of-plane deformation. The light field camera is also applied to 3D-DIC.
关键词： Digital zoom,Light field camera,3D-DIC,Digital refocus,Matching
更新于2025-09-23 15:22:29
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[IEEE 2018 26th European Signal Processing Conference (EUSIPCO) - Rome (2018.9.3-2018.9.7)] 2018 26th European Signal Processing Conference (EUSIPCO) - Ear Presentation Attack Detection: Benchmarking Study with First Lenslet Light Field Database
摘要： Ear recognition has received broad attention from the biometric community and its emerging usage in multiple applications is raising new security concerns, with robustness against presentation attacks being a very active field of research. This paper addresses for the first time the ear presentation attack detection problem by developing an exhaustive benchmarking study on the performance of state-of-the-art light field and non-light field based ear presentation attack detection solutions. In this context, this paper also proposes an appropriate ear artefact database captured with a Lytro ILLUM lenslet light field camera, including both 2D and light field contents, using several types of presentation attack instruments, including laptop, tablet and two different mobile phones. Results show very promising performance for two recent light field based presentation attack detection solutions originally proposed for face presentation attack detection.
关键词： Ear Presentation Attack Detection,Feature Extraction,Light Field Imaging,Artefact Database
更新于2025-09-23 15:22:29
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Light-Field Imaging for Plasma Wind-Tunnel Application
摘要： Limited optical access and high apparatus complexity are the main challenges for true three-dimensional (3-D) measurements in high-enthalpy plasma flows. However, with the advent of plenoptic cameras, the one-shot and single-camera acquisition of light-field data has become possible, enabling the 3-D analysis of complex scenes with one single optical access and one single exposure. So far, this technique has mostly been applied to problems containing opaque objects or particle-loaded flows. In this paper, approaches to explore the potential of light-field analysis for the 3-D investigation of brightly luminous, high-velocity plasma flows are presented. Using gas flames from a solder torch, the feasibility of plenoptic imaging of optically thin scenes is shown. The complete structure of the flame is derived from a single exposure. The transition of this approach to plasma-flow visualization is shown with very first acquisitions of a plasma freejet, including spectral filters for the measurement of the atomic oxygen distribution.
关键词： high-enthalpy flows,light-field imaging,plasma wind tunnel,plenoptic camera,3-D reconstruction
更新于2025-09-23 15:22:29
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Depth Estimation with Occlusion Handling from a Sparse Set of Light Field Views
摘要： This paper addresses the problem of depth estimation for every viewpoint of a dense light field, exploiting information from only a sparse set of views. This problem is particularly relevant for applications such as light field reconstruction from a subset of views, for view synthesis and for compression. Unlike most existing methods for scene depth estimation from light fields, the proposed algorithm computes disparity (or equivalently depth) for every viewpoint taking into account occlusions. In addition, it preserves the continuity of the depth space and does not require prior knowledge on the depth range. The experiments show that, both for synthetic and real light fields, our algorithm achieves competitive performance to state-of-the-art algorithms which exploit the entire light field and usually generate the depth map for the center viewpoint only.
关键词： light field,stereo matching,optical flow,low rank approximation,depth estimation
更新于2025-09-23 15:22:29