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Segmentation of Earth remote sensing images based on agglomerative pixel clustering using the minimum increment of the total squared error as a decision function

Segmentation of Earth remote sensing images based on agglomerative pixel clustering using the minimum increment of the total squared error as a decision function

I.G. Khanykov, V.A. Nenashev, M.V. Kharinov

Статья научная

Among cluster analysis methods applied to grayscale image segmentation, Arifin's algorithm is particularly notable. This algorithm enables partitioning the original image into a number of clusters ranging from N_max to 1 in linear time, where N_max represents the number of grayscale levels in the original image. Arifin's algorithm incrementally enlarges pixel clusters by combining a "minimum pair" at each iteration within the calculation cycle, characterized by the minimum distance Dist between clusters. The original method calculates Dist by taking the product of interclass and intraclass variances; however, this approach involves cumbersome formulas and lacks a quality assessment for the resulting partitions. This study introduces two modifications to Arifin's algorithm that simplify the calculation of Dist for identifying "minimum pairs" and performing cluster merging sequences, while also enabling evaluation of cluster partition quality. The first modification uses the increment of the total squared error as a distance function for Dist, whereas the second modification employs partial entropy. In the first approach, partition quality is evaluated based on the total squared error or standard deviation, while in the second, it is assessed by the information content. A computer program has been developed to implement the first modification of Arifin's algorithm, incorporating a difference formula to compute partition quality. This program has been tested using standard test images of various sizes, including full-scale aerospace images (three images at 1024×1024 pixels and one at 2050×2050 pixels). The practical significance of the modification, which leverages the increment of the total squared error to create a series of suboptimal piecewise-constant partitions, lies in reducing the number of operations per cycle needed to determine the "minimum pair" among all adjacent clusters, thereby halving processor time.

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Sensor with enhanced performance based on photonic crystal with a defect layer

Sensor with enhanced performance based on photonic crystal with a defect layer

Efimov I.M., Vanyushkin N.A., Golik S.S., Gevorgyan A.H.

Статья научная

We propose an improved structure of an optical biosensor based on a photonic crystal with a defect layer, which can detect the concentration of organic contaminants in water by defect mode shift. We investigated 4 types of defective photonic crystals with different arrangements of layers inside the perfect photonic crystals and their impact on the performance of the sensor. The sensitivity and amplitude of defect mode were examined as a function of defect layer thickness. Also, the peculiarities of edge modes in the presence of defect layer were investigated. Finally, we obtained a characteristic equation to determine the wavelengths of defect modes for an arbitrary 1D photonic crystal with an isotropic defect inside.

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Simulation of a long-haul fiber optic link with a two-mode optical fiber

Simulation of a long-haul fiber optic link with a two-mode optical fiber

Burdin Vladimir Alexandrovich, Bourdine Anton Vladimirovich

Статья научная

Modern telecommunication networks approach the capacity crunch, which is associated with the so-called nonlinear Shannon limit. So, the passage to fiber optic links with few-mode optical fibers is considered as an alternative solution of the described problem concerned with high nonlinearity of conventional commercial single-mode optical fibers. Presently, various designs of few-mode optical fibers have been known, with the recently published works presenting experimental results demonstrating their potentialities for long-haul fiber optic links. A lot of models of long-haul fiber optic links with few-mode optical fibers have been developed based on which features of a few-mode optical fiber transport network were numerically simulated. This work presents the results of simulation of a 6000-km long-haul fiber optic link with a two-mode optical fiber and 100-km-per-span Erbium doped fiber optic amplifiers system under 100 Gbps DP-DQPSK data transmission. We studied the use of particular linearly polarized modes and optical vortices for signal transmission. The computation results were compared with the simulation of the same fiber optic link with a single-mode optical fiber under the identical conditions.

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Simulation of forming processes with local heating of dual phase steels with use of laser beam shaping systems

Simulation of forming processes with local heating of dual phase steels with use of laser beam shaping systems

Bielak Robert, Bammer Ferdinand, Otto Andreas, Stiglbrunner Christian F., Colasse Claude, Murzin Serguei Petrovich

Статья научная

Features of laser-assisted warm forming of dual phase steel DP1000 are determined. Simulation of forming processes with local heating is performed. In the simulation procedure, the forming parameters of three dimensional forming were adapted to keep them within tolerable limits even in critical areas as well as identifying the localization and type of critical stresses. The capabilities of Abaqus were extended by use of the Python language to independently evaluate selected element strains, the position of deformed elements within the forming limit diagram and user-defined failure criteria. The simulation led to an adapted forming process permitting a significantly increased bulge forming depth by local laser heating of the forming zones. The developed simulation model shows a satisfactory conformity with experiments, performed using a fibre-coupled laser with a wavelength of 1070 nm and a maximum output power of 1500 W, and a servo bending press TRUMPF TruBend 7018. The required distribution of the laser beam energy can be obtained by using diffractive optical elements. The use of the model for technological operations opens up possibilities not only for the solution of the presented specific objective of laser assisted warm forming, but also for others applications.

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Simulation of the evolution of laser beams in impurity carbon nanotubes using the Madelung approach

Simulation of the evolution of laser beams in impurity carbon nanotubes using the Madelung approach

Kuvshinov E.A., Trofimov R.R., Konobeeva N.N.

Статья научная

The relevance of modeling the interaction of electromagnetic waves with various materials exhibiting nonlinear properties is increasing every year. In this work, we studied the dynamics of laser beams propagating in a medium of single-walled carbon nanotubes with impurities, placed in a dielectric. By multilevel impurity, we mean an impurity whose energy levels are separated from the conduction band and valence band in carbon nanotubes and lie inside the band gap of the dielectric medium. The novelty of this work lies in the development of a model for the evolution of electromagnetic radiation in the infrared range is constructed using the Madelung transform for the nonlinear Schrödinger equation, the numerical implementation of which is carried out using the smoothed-particle hydrodynamics. The influence of impurity parameters on the laser beam propagation in a given medium, namely, the energy of electron transitions from impurity levels to the first and second sublattices of nanotubes, is analyzed.

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Size effect of gold nanoparticles on optical and electrical properties of plasmonic silicon solar cell

Size effect of gold nanoparticles on optical and electrical properties of plasmonic silicon solar cell

Gulomov Jasurbek, Aliev Rayimjon, Gulomova Irodakhon

Статья научная

One of important tasks of the day is increasing the efficiency and decreasing the cost of the silicon solar cells. There is method of introducing of metal nanoparticles into solar cells to improve its absorption and reduce transmission as well as reflection coefficients. When metal nanoparticles are introduced into silicon solar cell, nanoplasmonic effect will occur. Nanoplasmonic effect lead to modification of light spectrum and generation of extra hot electrons. Nanoplasmonic effect strongly depends on size of nanoparticles. Therefore, in this paper, effect of gold nanoparticles size on properties of silicon solar cell has been studied by using simulation. Gold nanoparticles with sizes of 4 nm, 6 nm, 9 nm, 11 nm and 21 nm have been input into emitter region of silicon solar cell in order to use both of nanoplasmonic-electric and nanoplasmonic-optic effects for enhancing efficiency of silicon solar cell. Open circuit voltage didn’t change when size of nanoparticles has been changed from 4 nm to 11 nm. It dropped by 0.017 V when size of nanoparticles was 21 nm. Short circuit current has been maximum 6.7 mA/cm2 at nanoparticle size of 11 nm and minimum 3.1 mA/cm2 at nanoparticle size of 21 nm. It has been found from obtained results that gold nanoparticle with size of 11 nm affected significantly on properties of silicon solar cell. Besides, thickness of silicon solar cell can be decreased without dropping of efficiency by introducing gold nanoparticles. Because, main part of photons is absorbed near to metal nanoparticles inputted region.

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Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation

Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation

Dang N.H. Thanh, Nguyen Hoang Hai, Le Minh Hieu, Prayag Tiwari, V.B. Surya Prasath

Статья

Melanoma skin cancer is one of the most dangerous forms of skin cancer because it grows fast and causes most of the skin cancer deaths. Hence, early detection is a very important task to treat melanoma. In this article, we propose a skin lesion segmentation method for dermoscopic images based on the U-Net architecture with VGG-16 encoder and the semantic segmentation. Base on the segmented skin lesion, diagnostic imaging systems can evaluate skin lesion features to classify them. The proposed method requires fewer resources for training, and it is suitable for computing systems without powerful GPUs, but the training accuracy is still high enough (above 95 %). In the experiments, we train the model on the ISIC dataset – a common dermoscopic image dataset. To assess the performance of the proposed skin lesion segmentation method, we evaluate the Sorensen-Dice and the Jaccard scores and compare to other deep learning-based skin lesion segmentation methods. Experimental results showed that skin lesion segmentation quality of the proposed method are better than ones of the compared methods.

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Solving of the inverse diffraction problem in the first Rytov approximation for retrieving the phase object dielectric permittivity

Solving of the inverse diffraction problem in the first Rytov approximation for retrieving the phase object dielectric permittivity

Parkevich E.V., Khirianova A.I., Khirianov T.F.

Статья научная

In the study we derive a solution of the inverse diffraction problem aimed at retrieving the dielectric permittivity of a phase object by using the changes in the intensity and phase shift of coherent laser radiation probing the object. The theoretical considerations involve the results of solving the scalar Helmholtz wave equation in the first Rytov approximation. For an axisymmetric phase object probed with a plane wave, both with and without radiation absorption, computationally efficient equations are obtained, which reveal the relationship between the object dielectric permittivity and the Fourier spectra of the diffracted wave characteristics described in terms of the wave intensity and phase shift in free space. The equations provide reliable data when solving the inverse diffraction problem, since they take into account diffraction effects accompanying the wave passage through the object and enhancing in free space. Fundamental properties of the equations obtained are discussed together with their broad applications. The findings can open new perspectives in the diagnostics of various objects in different wavelength ranges.

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Solving the boundary artifact for the enhanced deconvolution algorithm suppose applied to fluorescence microscopy

Solving the boundary artifact for the enhanced deconvolution algorithm suppose applied to fluorescence microscopy

Toscani Micaela, Martnez Sandra

Статья научная

The SUPPOSe enhanced deconvolution algorithm relies in assuming that the image source can be described by an incoherent superposition of virtual point sources of equal intensity and finding the number and position of such virtual sources. In this work we describe the recent advances in the implementation of the method to gain resolution and remove artifacts due to the presence of fluorescent molecules close enough to the image frame boundary. The method was modified removing the invariant used before given by the product of the flux of the virtual sources times the number of virtual sources, and replacing it by a new invariant given by the total flux within the frame, thus allowing the location of virtual sources outside the frame but contributing to the signal inside the frame.

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Spatiotemporal ecosystem health assessment comparison under the pressure-state-response framework

Spatiotemporal ecosystem health assessment comparison under the pressure-state-response framework

Boori Mukesh Singh, Choudhary Komal, Paringer Rustam, Kupriyanov Alexander

Статья научная

A spatiotemporal ecosystem health (EH) assessment study is necessary for sustainable development and proper management of natural resources. At present higher rate of human-socio-economic activities, industrialization, and misuse of land are major factors for ecosystem degradation. Therefore this research work used remote sensing (RS) and geographical information system (GIS) technology, under pressure-state-response (PSR) framework with analytic hierarchy process (AHP) weight method based on 29 indicators were analyzed for spatiotemporal EH assessment in Tatarstan and Samara states in Russia from 2010 to 2020. Results indicate continuous degradation of EH in Tatarstan state while in Samara state first decreased and later on an improved ecosystem health condition. This is one of the most innovative analyses work for real-time accurate ecosystem health assessment, mapping, and monitoring as well as protect fragile eco-environment with sustainable development, proper policy-making, and management at any scale and region.

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Study on the Mainardi beam through the fractional Fourier transforms system

Study on the Mainardi beam through the fractional Fourier transforms system

Habibi Forouzan, Moradi Mohammad, Ansari Alireza

Статья научная

In this paper, we introduced the Mainardi beam and indicated its attributes under the Fractional Fourier transform for power variations of Fractional Fourier transform. The results represent that the behavior of the Mainardi beam is similar to that of the Airy beam. The obtained formula is a very powerful tool to describe propagation of a Mainardi beam through the FFT and the FrFT sys-tems. An analytical expression of the Mainardi beam passing through an Fractional Fourier trans-form system presented. The influences of the Fractional Fourier transform, rational order of the Mittag-Leffler function (Fourier transform of the Mainardi function) on the normalized intensity distribution and characteristics of the Mainardi beam in the Fractional Fourier transform system examined. Power of the Fractional Fourier transform (p) and rational order of the Mittag-Leffler function (q) control characteristics of the Mainardi beam such as effective beam size, number, width, height, and orientation of the beam spot.

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Study on the planning of rural land spatial utilization by improved particle swarm optimization

Study on the planning of rural land spatial utilization by improved particle swarm optimization

Yi Wenzhou

Статья научная

The planning of rural land space utilization is a very important problem. In this paper, the objective function of rural land use planning was analyzed firstly, and then the improved particle swarm optimization (IPSO) algorithm was obtained by improving the inertia weight for solution. The results showed that the land space use in the study area was more reasonable after the planning based on the IPSO algorithm, the forest land and construction land increased, the area of grassland, cultivated land and water area reduced appropriately, the aggregation degree of all types of land improved, and the space distribution was more planned, which was more conducive to production activities. The analysis results verify the effectiveness of the IPSO method in land space use planning, which can improve the efficiency and benefit of land space use, and it can be popularized in practical application.

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Subcarrier wave continuous-variable quantum key distribution with Gaussian modulation: composable security analysis

Subcarrier wave continuous-variable quantum key distribution with Gaussian modulation: composable security analysis

Goncharov Roman Konstantinovich, Kiselev Alexei Donislavovich, Samsonov Eduard Olegovich, Egorov Vladimir Ilyich

Статья научная

In this paper, we continue the study of the quantum cryptographic GG02 protocol, performed using the approach based on the subcarrier waves. We modify the scheme via heterodyne detection and perform security analysis for the full trusted hardware noise model in the presence of collective attacks with finite-key effects. It is shown that the system can potentially distribute the key even if the level of losses in the channel is above 9 dB. This result is consistent with the general technical level and comply with modern standards of practical CV-QKD systems. Finally, the system under consideration fully meets the criterion of composability.

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Super-resolution microscopy based on interpolation and wide spectrum de-noising

Super-resolution microscopy based on interpolation and wide spectrum de-noising

Cheng T., Chenchen T.

Статья научная

In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function. Such a raw image is referred to herein as a conventional raw image, based on which better single molecule localization effect and efficiency can be achieved. It is found that both interpolation and de-noising can effectively improve the Signal to Noise Ratio of the conventional raw image. The conventional raw image, the de-noised, the interpolated and the de-noised interpolated are compared and analyzed and compressed sensing is used for super-resolution reconstruction. The simulation results show that both the highest Signal to Noise Ratio and the best super-resolution reconstruction can be obtained by de-noising the interpolated conventional raw image. This method also renders the best super-resolution reconstruction and minimum gradient in the real experiment. De-noising the interpolated conventional raw image is an effective method to improve the super-resolution microscopy.

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Super-resolution microscopy based on wide spectrum denoising and compressed sensing

Super-resolution microscopy based on wide spectrum denoising and compressed sensing

Cheng Tao, Jin Hu

Статья научная

WSD can effectively remove random noise of a raw image from very low density to ultra-high density fluorescent molecular distribution scenarios. The size of the raw image that WSD can denoise is subject to the used measurement matrix. A large raw image must be divided into blocks so that WSD denoises each block separately. Based on traditional single-molecule localization and super-resolution reconstruction scenarios, wide spectrum denoising (WSD) for blocks of different sizes was studied. The denoising ability is related to block sizes. The general trend is when the block gets larger, the denoising effect gets worse. When the block size is equal to 10, the denoising effect is the best. Using compressed sensing, only 20 raw images are needed for reconstruction. The temporal resolution is less than half a second. The spatial resolution is also greatly improved.

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Switching median filter for suppressing multi-pixel impulse noise

Switching median filter for suppressing multi-pixel impulse noise

Trubitsyn Andrey Afanasievich, Grachev Evgeny Yurievich

Статья научная

This paper proposes a new switching median filter for suppressing multi-pixel impulse noise in X-ray images. A multi-pixel impulse is understood as a set of several neighboring pixels, the intensity of each significantly exceeds background intensity. Multi-pixel noise can occur, for example, due to the blooming effect, the reason being the limited value of pixel saturation capacity. This article defines the thresholds for the intensity increment relative to the eight immediate neighbors, above which the current pixel is processed by the median filter. The dependence of these thresholds on the number of pixels in an impulse is presented. The proposed algorithm is based on the median filtering process, which consists of several iterations. In this case, the filter has the smallest possible size, which minimizes image distortion during processing. In particular, to exclude a single-pixel impulse, pixel processing is turned on when intensity surge exceeds 3.5 with the grayscale value ranging from 0 to 1. At the same time, to exclude nine-pixel impulses, three iterations are required with the following thresholds: the first iteration with a threshold 2.0; the second iteration also with a threshold 2.0 and the third iteration with a threshold 3.5. The algorithm proposed was tested on real X-ray images corrupted by multi-pixel impulse noise. The algorithm is not only simple, but also reliable and suitable for real-time implementation and application. The efficiency of the technique is shown in comparison with other known filtering methods with respect to the degree of noise suppression. The main result of the testing is that only the proposed method allows excluding multi-pixel noise. Other advantage of the algorithm is its weak effect on the level of Gaussian noise leading to the absence of image blurring (or preserving image details) during processing.

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Synthesis of stochastic algorithms for image registration by the criterion of maximum mutual information

Synthesis of stochastic algorithms for image registration by the criterion of maximum mutual information

Tashlinskii A.G., Safina G.L., Ibragimov R.M.

Статья научная

We discuss a synthesis of stochastic algorithms, obtaining expressions for gradients of Shannon, Renyi and Tsallis mutual information on the basis of the mathematical apparatus of stochastic gradient adaptation of algorithms for estimating image registration parameters. To obtain the expressions, derivatives of the image entropy with respect to the estimated parameters are used. The entropies are calculated using a Parzen window method. A comparative study of the synthesized algorithms in terms of stability and accuracy of the registration parameter estimates, including in conditions of additive noise, is carried out.

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Testing edible oil authenticity by using smartphone based spectrometer

Testing edible oil authenticity by using smartphone based spectrometer

Mai Hanh Hong, Le Tran Thinh

Статья научная

In recent years, there has been an increasing interest in the classification of edible vegetable oils, examining authenticity and in detecting possible adulteration of high quality, expensive extra virgin olive oils with low-cost edible oils. Classical methods such as gas chromatography, liquid chromatography, Fourier transform infrared and nuclear magnetic resonance, mass spectrometry, and Raman spectroscopy have been widely applied to examine the authenticity of edible oils. Despite of their high sensitivity and accuracy, these methods are significantly expensive for daily life testing, especially in resource-poor regions. Furthermore, they are time-consuming as samples have to be analyzed in dedicated laboratories. In this paper, we propose a compact, low-cost, portable smartphone-based spectrometer for testing edible oil authenticity. Using simple laboratory optical components and a smartphone, we developed a compact spectrometer which can function in the wavelength range of 400-700 nm with the spectrum/pixel resolution of 0.334 nm / pixel...

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The basic assembly of skeletal models in the fall detection problem

The basic assembly of skeletal models in the fall detection problem

Seredin Oleg Sergeevich, Kopylov Andrei Valerievich, Surkov Egor Eduardovich, Huang Shih-Chia

Статья научная

The paper considers the appliance of the featureless approach to the human activity recognition problem, which exclude the direct anthropomorphic and visual characteristics of human figure from further analysis and thus increase the privacy of the monitoring system. A generalized pairwise comparison function of two human skeletal models, invariant to the sensor type, is used to project the object of interest to the secondary feature space, formed by the basic assembly of skeletons. A sequence of such projections in time forms an activity map, which allows an application of deep learning methods based on convolution neural networks for activity recognition. The proper ordering of skeletal models in a basic assembly plays an important role in secondary space design. The study of ordering of the basic assembly by the shortest unclosed path algorithm and correspondent activity maps for video streams from the TST Fall Detection v2 database are presented.

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