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- 摘要
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- 实验方案
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Analysis of full disc Ca II K spectroheliograms
摘要： Context. Historical Ca II K spectroheliograms (SHG) are unique in representing long-term variations of the solar chromospheric magnetic field. They usually suffer from numerous problems and lack photometric calibration. Thus accurate processing of these data is required to get meaningful results from their analysis. Aims. In this paper we aim at developing an automatic processing and photometric calibration method that provides precise and consistent results when applied to historical SHG. Methods. The proposed method is based on the assumption that the centre-to-limb variation of the intensity in quiet Sun regions does not vary with time. We tested the accuracy of the proposed method on various sets of synthetic images that mimic problems encountered in historical observations. We also tested our approach on a large sample of images randomly extracted from seven different SHG archives. Results. The tests carried out on the synthetic data show that the maximum relative errors of the method are generally <6.5%, while the average error is <1%, even if rather poor quality observations are considered. In the absence of strong artefacts the method returns images that differ from the ideal ones by <2% in any pixel. The method gives consistent values for both plage and network areas. We also show that our method returns consistent results for images from different SHG archives. Conclusions. Our tests show that the proposed method is more accurate than other methods presented in the literature. Our method can also be applied to process images from photographic archives of solar observations at other wavelengths than Ca II K.
关键词： Sun: activity,Sun: chromosphere,Sun: faculae, plages,techniques: image processing
更新于2025-09-23 15:21:01
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Enhanced Clean-In-Place Monitoring Using Ultraviolet Induced Fluorescence and Neural Networks
摘要： Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.
关键词： monitoring,image processing,resource efficiency,neural network,fluorosensing
更新于2025-09-23 15:21:01
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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) - HESCNET: A Synthetically Pre-Trained Convolutional Neural Network for Human Embryonic Stem Cell Colony Classification
摘要： This paper proposes a method for improving the results of deep convolutional neural network classification using synthetic image samples. Generative adversarial networks are used to generate synthetic images from a dataset of phase-contrast, human embryonic stem cell (hESC) microscopy images. hESCnet, a deep convolutional neural network is trained, and the results are shown on various combinations of synthetic and real images in order to improve the classification results with minimal data.
关键词： Image Processing,Generative Adversarial Networks,Deep Learning,Computer Vision,Video Bioinformatics
更新于2025-09-23 15:21:01
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European Microscopy Congress 2016: Proceedings || New Opportunities in multi-frame STEM Spectroscopy & Fractional Beam-current EELS
摘要： The paper discusses the application of multi-frame super-resolution techniques in the field of optoelectronics, specifically focusing on the enhancement of image quality through the use of advanced algorithms and hardware. It explores the limitations and potential improvements in current methodologies, presenting a novel approach to image processing that leverages both software and hardware innovations.
关键词： hardware acceleration,super-resolution,image processing,multi-frame,optoelectronics
更新于2025-09-23 15:21:01
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[Energy, Environment, and Sustainability] Advances in Solar Energy Research || Solar Radiation Assessment and Forecasting Using Satellite Data
摘要： Since the availability of ground data is very sparse, satellite data provides an alternative method to estimate solar irradiation. Satellite data across various spectral bands may be employed to distinguish weather signatures, such as dust, aerosols, fog, and clouds. For a tropical country like India, which is potentially rich in solar energy resources, the study of these parameters is of crucial importance from the perspective of solar energy. Furthermore, a complete utilization of the solar energy depends on its proper integration with power grids. Because of its variable nature, incorporation of photovoltaic energy into electricity grids suffers technical challenges. Solar radiation is subjected to reflection, scattering and absorption by air molecules, clouds, and aerosols in the atmosphere. Clouds can block most of the direct radiation. Modern solar energy forecasting systems rely on real-time Earth observation from the satellite for detecting clouds and aerosols.
关键词： Image processing,GHI,Numerical weather prediction,Forecasting
更新于2025-09-23 15:21:01
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Searching for Subsecond Stellar Variability with Wide-field Star Trails and Deep Learning
摘要： We present a method that enables wide-field ground-based telescopes to scan the sky for subsecond stellar variability. The method has operational and image processing components. The operational component takes star trail images. Each trail serves as a light curve for its corresponding source and facilitates subexposure photometry. We train a deep neural network to identify stellar variability in wide-field star trail images. We use the Large Synoptic Survey Telescope Photon Simulator to generate simulated star trail images and include transient bursts as a proxy for variability. The network identifies transient bursts on timescales down to 10 ms. We argue that there are multiple fields of astrophysics that can be advanced by the unique combination of time resolution and observing throughput that our method offers.
关键词： techniques: image processing,methods: observational,techniques: photometric
更新于2025-09-23 15:21:01
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[EAI/Springer Innovations in Communication and Computing] Applications of Intelligent Technologies in Healthcare || Survey Analysis of Automatic Detection and Grading of Cataract Using Different Imaging Modalities
摘要： Automatic detection and grading of cataract alleviate the burden of ophthalmologists and clinicians. It also provides an objective way to measure the severity of cataract and helps reduce the vision loss by timely and accurate diagnosis. In this survey-based paper, we presented an overview of the methods and techniques developed for cataract detection and gradation. We mainly investigated the usage of four types of imaging modalities used for automatic diagnosis of cataract using digital image processing. These types include slit-lamp images, retro-illumination images, retinal images, and digital eye images. We also discuss the shortcomings of these methods and future research possibilities to improve these methods.
关键词： automatic detection,imaging modalities,digital image processing,grading,cataract
更新于2025-09-23 15:21:01
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Automatic lung segmentation in low-dose chest CT scans using convolutional deep and wide network (CDWN)
摘要： Computed tomography (CT) imaging is the preferred imaging modality for diagnosing lung-related complaints. Automatic lung segmentation is the most common prerequisite to develop a computerized diagnosis system for analyzing chest CT images. In this paper, a convolutional deep and wide network (CDWN) is proposed to segment lung region from the chest CT scan for further medical diagnosis. Earlier lung segmentation techniques depend on handcrafted features, and their performance relies on the features considered for segmentation. The proposed model automatically segments the lung from complete CT scan in two laps: (1) learning the required ?lters to extract hierarchical feature representations at convolutional layers, (2) dense prediction with spatial features through learnable deconvolutional layers. The model has been trained and evaluated with low-dose chest CT scan images on LIDC-IDRI database. The proposed CDWN reaches the average Dice coef?cient of 0.95 and accuracy of 98% in segmenting the lung regions from 20 test images and maintains consistent results for all test images. The experimental results con?rm that the proposed approach achieves a superior performance compared to other state-of-the-art methods for lung segmentation.
关键词： Medical imaging,Image processing and analysis,Deep learning,Automatic lung segmentation,Convolutional neural network
更新于2025-09-23 15:21:01
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Comparison of AlGaInAs-Based Laser Behavior Grown on Hybrid InP-SiOa??/Si and InP Substrates
摘要： Processing large very high-resolution remote sensing images on resource-constrained devices is a challenging task because of the large size of these data sets. For applications such as environmental monitoring or natural resources management, complex algorithms have to be used to extract information from the images. The memory required to store the images and the data structures of such algorithms may be very high (hundreds of gigabytes) and therefore leads to unfeasibility on commonly available computers. Segmentation algorithms constitute an essential step for the extraction of objects of interest in a scene and will be the topic of the investigation in this paper. The objective of the present work is to adapt image segmentation algorithms for large amounts of data. To overcome the memory issue, large images are usually divided into smaller image tiles, which are processed independently. Region-merging algorithms do not cope well with image tiling since artifacts are present on the tile edges in the ?nal result due to the incoherencies of the regions across the tiles. In this paper, we propose a scalable tile-based framework for region-merging algorithms to segment large images, while ensuring identical results, with respect to processing the whole image at once. We introduce the original concept of the stability margin for a tile. It allows ensuring identical results to those obtained if the whole image had been segmented without tiling. Finally, we discuss the bene?ts of this framework and demonstrate the scalability of this approach by applying it to real large images.
关键词： Image processing,image segmentation,region merging,scalability,image tiling
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - PolySi Based Passivating Contacts Enabling Industrial Silicon Solar Cell Efficiencies up to 24%
摘要： An RF argon plasma jet has been explored using high-speed camera imaging at 10 000 frames/s. Small variations of gas ?ow and/or RF power lead to instabilities of the ?lament movement. Two types of instabilities have been observed depending on the interrelated azimuthal velocities of ?laments. In the case of antiparallel ?lament velocities, one ?lament is collapsing and fuses with the other ?lament, while the collapsing ?lament exhibits a striated structure. In the case of parallel velocities, both ?laments establish a symmetric con?guration and rotate with constant velocity in the jet. Spatially and temporally resolved features are visualized with a time-colored stroboscopic image.
关键词： plasma stability,plasma materials processing,Image processing
更新于2025-09-23 15:19:57