Статьи журнала - Компьютерная оптика
Все статьи: 2511
Convolutional Neural Network-Based Low Light Image Enhancement Method
Статья научная
Low-light image augmentation has become increasingly important with the advancement of computer vision technologies in a variety of application settings. However, noise and contrast reduction frequently have an impact on image quality in low-light situations. In this paper, a convolutional neural network-based technique for low-light picture augmentation is put forth. The stability of local binary features under variations in illumination is the study’s initial method of providing directional advice for the enhancement algorithm. Second, the addition of a channel attentiveness mechanism improves the network’s capacity to acquire low-light image features. The proposed model of the study performed better on average in the two dataset tests when compared to the contrast-constrained adaptive histogram equalization algorithm and the bilateral filtering algorithm. Additionally, the recall and DICE coefficient performed better in the tests as well, improving by 16.24 % and 4.98 %, respectively. The proposed method outperformed all others in the picture enhancement studies, according to the experimental findings, proving the validity of this study. The purpose of the study is to offer a reference framework for low-light image enhancing techniques.
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Convolutional Neural Network-Based Low Light Image Enhancement Method
Статья научная
With advances in science and technology, remote sensing images are vital for vegetation monitoring. The use of remote sensing allows for the collection of widespread, multi-temporal data on vegetation, leading to a better comprehension and management of natural resources. In this study, a new remote sensing image recognition model is proposed by combining the filtering algorithm to reconstruct the time series curve, fusing the quadratic difference method and decision tree, and introducing the morphological similarity distance method. The results of the experiment indicate that the normalized vegetation index in towns was consistently higher than the index in bodies of water throughout the year. The normalized index for water was generally close to or below 0. Additionally, the normalized index for forests surpassed that of both water and towns. Although the waveforms for all three were similar, the differences were significant. Notably, the forest normalized index curves had a single peak with a noteworthy duration. The study found that the mapping accuracy for fall plants was highest in 2013 (97.37 %) and lowest in 2014 (80.00 %). Similarly, for spring vegetation, the mapping accuracy was greatest in 2017 (97.96 %) and lowest in 2014, but still favorable at 90.00 %. These results highlight the high advantages of the remote sensing identification method proposed by the study for vegetation identification, which is crucial for natural resource management and environmental protection.
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Copy move forgery detection using key point localized super pixel based on texture features
Статья научная
The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transform (SIFT) based key point extraction. The experimental result indicates the proposed KLSP approach achieves better performance than the previous well known approaches.
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Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
Статья научная
Crop growth monitoring is an important phenomenon for agriculture classification, yield estimation, agriculture field management, improve productivity, irrigation, fertilizer management, sustainable agricultural development, food security and to understand how environment and climate change effect on crops especially in Russia as it has a large and diverse agricultural production. In this study, we assimilated monthly crop phenology from January to December 2018 by using the NDVI time series derived from moderate to high Spatio-temporal resolution Sentinel and Landsat data in cropland field at Samara airport area, Russia. The results support the potential of Sentinel and Landsat data derived NDVI time series for accurate crop phenological monitoring with all crop growth stages such as active tillering, jointing, maturity and harvesting according to crop calendar with reasonable thematic accuracy. This satellite data generated NDVI based work has great potential to provide valuable support for assessing crop growth status and the above-mentioned objectives with sustainable agriculture development.
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Cross-layer optimization technology for wireless network multimedia video
Статья научная
With the development of communication technology, wireless Internet has become more and more popular. The traditional network layered protocols cannot meet the increasingly rich network services, especially video. This paper briefly introduced the cross-layer transmission of video in wireless network and the cross-layer optimization algorithm used for improving video transmission quality and improved the traditional cross-layer algorithm. Then, the two cross-layer algorithms were simulated and analyzed on MATLAB software. The results showed that the packet delivery rate, peak signal to noise ratio and downlink throughput of the improved cross-layer algorithm were significantly higher than those of the traditional cross-layer algorithm under the same signal to interference plus noise ratio of receiving users in wireless network; meanwhile, with the increase of signal to interference plus noise ratio of the receiving user, the packet delivery rate and peak signal to noise ratio of the two algorithms increased, and tended to be stable after some signal to interference plus noise ratio, while the throughput of the two algorithms increased linearly. In the established real wireless network, the package delivery rate, peak signal to noise ratio and throughput of video after application of cross-layer algorithm were significantly improved, and the wireless network applying the improved cross-layer algorithm improved more. In summary, compared with the traditional cross-layer algorithm, the improved cross-layer algorithm can better improve the transmission quality of video in wireless network.
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Статья научная
The work is devoted to an overview of the current state of optoacoustic fiber-optic ultrasonic transducers based on thermoelastic effect and fiber-optic interference receivers, its scope, technologies and materials used, the advantages and disadvantages of different methods and the prospects for the development of the industry.
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Cравнение разных подходов к формированию «идеального» оптического вихря
Статья научная
Получены точные аналитические выражения, описывающие комплексную амплитуду идеального оптического вихря, сформированного тремя разными оптическими элементами: амплитудно-фазовым с пропусканием, пропорциональным функции Бесселя, оптимальным фазовым с пропусканием, равным знаковой функции от функции Бесселя, и вихревым аксиконом. Показано, что интенсивность света на кольце больше для оптимального фазового элемента. Ширина светового кольца, сформированного вихревым аксиконом, примерно в два раза больше, чем ширина двух других колец. Таким образом, оптимальный элемент является наилучшим кандидатом для формирования идеального оптического вихря. Результаты моделирования подтверждают теоретические выводы, а результаты эксперимента согласуются с теорией и результатами моделирования.
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Cуперпозиция оптического вихря и плоской волны с линейными поляризациями в остром фокусе
Статья научная
Рассмотрена острая фокусировка суперпозиции вихревого лазерного пучка с топологическим зарядом n с линейной поляризацией и плоской волны с такой же линейной поляризацией, направленной вдоль горизонтальной оси. В формализме Ричардса–Вольфа получены аналитические выражения для распределения интенсивности и продольной проекции спинового углового момента в плоскости фокуса. Показано, что для четных и нечетных номеров n интенсивность и спиновый угловой момент обладают разной симметрией: при четном n они симметричны относительно обеих декартовых осей, а при нечетном n они симметричны только относительно вертикальной оси. Распределение интенсивности имеет 2n локальных максимумов в фокусе, и на оптической оси интенсивность при любом n отлична от нуля. Распределение продольной проекции спинового углового момента (плотность спина) в плоскости фокуса имеет (n+2) субволновых областей с положительным спиновым угловым моментом и (n+2) областей с отрицательным спиновым угловым моментом, центры которых, чередуясь, лежат на окружности некоторого радиуса с центром на оптической оси. Такое распределение спина с разным знаком демонстрирует продольный спиновый эффект Холла в фокусе. Суммарно в фокусе отрицательный и положительный спин взаимно компенсируется и равен нулю.
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DFW-YOLO: A small insulator target defect detection algorithm based on improved YOLOv8s
Статья научная
With the continuous progress of deep learning technology, UAV aerial photography faces significant challenges for insulator defect detection. Aiming at the problems of low detection accuracy of existing target detection algorithms and difficulty in recognizing small target defects, we propose an improved small target insulator defect detection algorithm based on YOLOv8s, named DFW-YOLO. Firstly, the Detect_Efficient lightweight detection header is proposed using partial convolution (PConv) to lighten the original detection header. Secondly, a FocalModulation focal modulation module is introduced into the backbone network to enhance the model’s extraction and fusion capabilities for features at different scales. Finally, to enhance the model’s focus on poor-quality samples and reduce the harmful gradients they produce, a loss function with a Wise-IoU V3 dynamic non-monotonic focusing mechanism is used instead of the original CIOU loss function. We conducted experiments on a publicly available dataset of UAV aerial photography. According to the experimental data, DFW-YOLO achieves an 86.8% mAP in insulator defect detection, showing a 6.8% improvement compared to the original YOLOv8s model and generally exceeding the performance of other prominent models. Utilizing this method can effectively boost the accuracy of identifying insulator defects in small targets.
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Data mining of corporate financial fraud based on neural network model
Статья научная
Under the active market economy, more and more listed companies emerge. Because of the various interest relationships faced by listed companies, some enterprises which are not well managed or want to enhance company’s value will choose to forge financial reports by improper means. In order to find out the false financial reports as accurately as possible, this paper briefly introduced the relevant indicators for judging the fraudulence of financial reports of listed companies and the recognition model of financial reports based on back propagation (BP) neural network. Then the selection of the input relevant indexes was improved. The improved BP neural network was simulated and analyzed in MATLAB software and compared with the traditional BP neural network and support vector machine (SVM). The results showed that the importance of total assets net profit, earnings per share, cash reinvestment rate, operating gross profit and pre-tax ratio of profit to debt was the top 5 among 20 judgment indexes. In the identification of testing samples of financial report, the accuracy, precision, recall rate and F value all showed that the performance of the improved BP neural network was better than that of the traditional BP network and SVM.
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Статья научная
The purpose of research to create automated personalization of diabetic macular edema laser treatment. The results are based on analysis of large semi-structured data, methods and algorithms for fundus image processing. The technology improves the quality of retina laser coagulation in the treatment of diabetic macular edema, which is one of the main reasons for pronounced vision decrease. The proposed technology includes original solutions to establish an optimal localization of multitude burns by determining zones exposed to laser. It also includes the recognition of large amount of unstructured data on the anatomical and pathological locations' structures in the area of edema and data optical coherent tomography. As a result, a uniform laser application on the pigment epithelium of the affected retina is ensured. It will increase the treatment safety and its effectiveness, thus avoiding the use of more expensive treatment methods. Assessment of retinal lesions volume and quality will allow predicting the laser photocoagulation results and will contribute to the improvement of laser surgeon's skills. The architecture of a software complex comprises a number of modules, including image processing methods, algorithms for photocoagulation pattern mapping, and intelligent analysis methods.
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Статья научная
Our study aimed to develop a comprehensive system for discriminating between benign and malignant breast lesions on ultrasound images. The system integrated deep learning (DL) and conventional machine learning techniques. Our database consisted of 494 ultrasound images, comprising 231 benign and 263 malignant breast lesions. In the initial stage, we evaluated the performance of non-modified DL networks, including VGG-16, ResNet-18, and InceptionRes-NetV2. We assessed the results for the entire lesion as well as its inner and outer parts. For training the networks, we employed supervised transfer learning. In the second stage, we utilized a support vector machine (SVM) model for lesion classification. The features obtained from the modified DL networks, where we removed the last layers, were used for training and testing the SVM. In the final stage, we assessed the classification results using SVM, with a focus on selecting the most significant features obtained from the modified DL networks. We employed techniques such as ReliefF, FSCNCA, and LASSO for feature selection. Our three-step approach yielded impressive results, with an accuracy of 0.987, sensitivity of 0.989, and specificity of 0.983. These results significantly outperformed using only DL or DL+SVM without feature selection. Overall, our algorithm demonstrated sufficient accuracy in the clinical task of discriminating between benign and malignant breast lesions on ultrasound images.
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Статья научная
We propose and numerically verify a design of the photonic integrated circuit for in-plane generation of a 1st azimuthal order vortex mode in dielectric rectangular waveguides. Radiation is introduced into the proposed structure in a standard way through two grating couplers. Applying a mode coupling and specific phase shift, a field with the required amplitude-phase distribution is formed directly in the output waveguide. The geometric dimensions of the device are simulated and optimized to fit the technological parameters of the silicon-on-insulator platform.
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Design and optimization of high-contrast gratings for multispectral VCSEL-SOI laser sources
Статья научная
In the scope of a computational experiment, high-contrast gratings (HCG) formed on a silicon-on-insulator (SOI) platform within vertical-cavity surface-emitting lasers (VCSELs) were studied for multispectral laser sources. A simulation model for spectral characteristics calculation is proposed, which includes two heterogeneously integrated parts of the VCSEL: 1) the lower output mirror based on a HCG grating in the silicon layer of the SOI surrounded by air cavities to enhance the contrast of the HCG; 2) the semiconductor VCSEL structure with an air aperture for current and optical confinement. Comparative analysis results of the spectral characteristics of VCSEL-SOI structures for zeroth, first, and second-order modes, which can be excited in the air aperture of the VCSEL, are presented. It is demonstrated that the HCG, acting as one of the cavity mirrors, effectively discriminates the VCSEL higher-order modes. An algorithm for calculating HCG parameters that ensure the maximum reflectivity at a fixed thickness of the silicon layer of the SOI is developed.
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Статья научная
The paper proposes a new architecture for the photonic laboratory-on-a-chip sensing systems, where multiple sensors based on microring resonators (MRR) are fed by a MRR with low quality factor, working as a spectrum shaper. This architecture enables simultaneous intensity scanning of at least four MRR-based sensors on the silicon-on-insulator platform. We evaluated numerically the system’s sensitivity for various schemes of connecting the sensors and the spectrum shaper. The sensor’s sensitivity was 110 nm/RIU. The sensing system configuration largely determines its sensitivity, which reaches 1980 dB/RIU. The considered architecture may be useful for implementing fully integrated optical lab-on-a-chip structures, as well as distributed multichannel sensing systems.
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Design of a home video behavior recognition system based on visual privacy security mechanism
Статья научная
The rapid development of the Internet and advanced technology has brought great convenience to people’s lives; However, real-time video and other privacy information obtained from computers can be leaked, resulting in economic losses and not conducive to the construction of computer network security. In response to the above issues, this study introduces compressed perception theory and temporal adaptive modules to achieve visual shielding, and based on this, designs a home video behavior system based on visual privacy security mechanism. The research results show that in the comparison of measurement matrices at different levels, the Bernoulli random matrix has the highest recognition accuracy, with recognition accuracy rates of 100 %, 98.73 %, 98.76 %, and 85.62 % from the first layer to the fourth layer, respectively. In the recognition performance results of different video behavior recognition systems in the YouTube database, UCF Sports database, and Hollywood2 database, the average recognition accuracy of the proposed system is the highest in most cases, with 94.6 %, 73.5 %, and 77.1 %, respectively. In summary, the system proposed in the study can achieve accurate recognition of home video behavior after visual masking, and has good results in practical applications.
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Design of lenses for the focusing into a line
Статья научная
A method for designing a curvilinear lens for focusing into a line is proposed. The obtained solutions represent a complex refracting surface in an analytical form expressed through the eikonal distribution along the line. The calculation of a 3-D lens focusing into a line-segment is reduced to a simple design of cylindrical profile with required function of ray-correspondence.
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Design, simulation, and fabrication of silicon-on-insulator MEMS vibratory decoupled gyroscope
Статья научная
This paper reports the design and fabrication of a 2-degree-of-freedom (DOF) decoupled vibratory gyroscope based on a silicon-on-insulator (SOI) MEMS process. The 2-DOF capacitive comb structure is deliberately designed to have a decoupled drive and sense mode oscillation to prevent the unstable operation due to mechanical coupling, resulting in a low zero rate out-put drift. It is well known that the closer are the drive and sense resonances, the higher is the angular rate resolution of the gyroscope. Generally, this is achieved by using symmetric suspensions, but it results in a reduced bandwidth. The proposed design has been configured to achieve a bandwidth of about 150 Hz, while ensuring the decoupled operation of the drive and sense modes. An analytical method has been employed to study the steady state response of the 2-DOF structure. FEM analysis has been carried out in CoventorWare® MEMS Design software and the simulation results show that the drive resonance occurs at 21.48 kHz and sense resonance at 21.63 kHz, which are in close agreement with the theoretical results. The structure is designed with a 15 µm thick device layer. Fabrication of the design is proposed using a two mask process based on Deep reactive-ion etching (DRIE) and sacrificial wet release etching on a SOI wafer. DRIE etching with an aspect ratio of 1:5 has been successfully carried out as desired and the results have been presented.
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Designing multilayer dielectric filter based on TiO2/SiO2 for fluorescence microscopy applications
Статья научная
This study presents a new construction design of a distributed Bragg reflector (DBR) filter and a Fabry-Pérot (FP) filter by using needle technique as a synthesis method. The optimized DBR and FP filters having a proper number of layers with controlling thickness TiO2/SiO2 are utilized to transmit only a certain narrow band of wavelengths while blocking the others. As a proof of concept, the filters are designed to selectively transmit only a very narrow band of wavelength at 780 nm which is the near infrared (NIR) fluorescent emission from Alexa Fluor 750 dye. The obtained results show that the optimized filters represent advanced spectral performance which can be used to improve the sensitivity and the imaging contrast in fluorescence microscopy.
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