Computer Optics

16-26

Authors: V.V. Nikolaev, E.I. Girshova, M.A. Kaliteevski

We propose a method of analysis of spontaneous emission of a quantum emitter (an atom, a luminescence center, a quantum dot) inside or in vicinity of a cylinder. At the focus of our method are analytical expressions for the scattering matrix of the cylindrical nanoobject. We propose the approach to electromagnetic field quantization based of eigenvalues and eigenvectors of the scattering matrix. The method is applicable for calculation and analysis of spontaneous emission rates and angular dependences of radiation for a set of different systems: semiconductor nanowires with quantum dots, plasmonic nanowires, cylindrical hollows in dielectrics and metals. Relative simplicity of the method allows obtaining analytical and semi-analytical expressions for both cases of radiation into external medium and into guided modes.

36-39

Authors: S.S. Stafeev, A.D. Pryamikov, G.K. Alagashev, V.V. Kotlyar

In this paper, the propagation of a second-order cylindrical vector beam in gradient-index and microstructured fibers is numerically simulated using the RSoft Fullwave software. The second-order vector beams are shown to be vector modes of these fibers. In the calculated fundamental modes, regions are found in which there is an energy flow directed oppositely to the beam propagation direction (regions of a reverse energy flow). The absolute value of the longitudinal component of the reverse energy flow is found to be much lower than that of the forward flow.

48-52

Authors: K.M. Bulatov, P.V. Zinin, A.A. Bykov, I.V. Malykhina

In this report we describe a fast 3-color method of the measurement of temperature distributions on a surface of a heated solid using a RGB color camera with a high frame rate (100 images per second). Statistical error the RGB method is not high, and do not exceed around 5.5% which is surprising taking in to account the number of the measurements at each pixel. Comparison of the results of the temperature measurements on a tungsten plate heated by infra-red laser radiation and conducted with this technique and those obtained with the acousto-optical tunable filter technique demonstrate that error of the temperature measured by 3-color method is only two times as high as that of the tandem acousto-optic filter technique method.

62-67

Authors: S.I. Kharitonov, V.S. Pavelyev, N.L. Kazanskiy, Y.S. Strelkov, K.N. Tukmakov, A.S. Reshetnikov, S.V. Ganchevskaya, V.V. Gerasimov, B.A. Knyazev

A problem of optimizing the subwavelength microrelief of a binary cylindrical transmissive diffractive lens (DL) with a 300-mm focal length for a wavelength of λ=141 μm was considered. High-resistivity silicon was chosen as the DL substrate material. The angle of incidence of the illuminating beam was taken to be π/6. The optimization parameters were the height of the DL profile and the fill factor of the groove. The main goal of optimizing the design was to increase the diffraction efficiency of the lens. The DL diffraction efficiency was calculated using a Fourier mod method. The DL was fabricated by plasma-chemical etching (Bosch process) of the surface of a silicon substrate. The diffraction efficiency of the calculated lens was estimated to be 70%. However, a full-scale experiment showed the real efficiency to be much lower. These differences are related to both errors in the manufacturing process of the DL and non-ideal thickness parameters of the silicon wafers.

79-91

Authors: N.N. Vasilyuk

A rotational blur correction algorithm is considered as the initial stage of image processing in the problem of attitude measurement using a star tracker. To implement this algorithm, the star tracker must be equipped with a three-axis gyroscope. The algorithm does not guarantee the detection of an image of a star against the background of the daytime sky in one frame but facilitates conditions for subsequent image stacking. The correction aims to localize energy maxima of the blurred star images in pixels with predetermined characteristics. The correction highlights these pixels against the background and improves the signal-to-noise ratio, though deteriorating the artistic quality of the whole digital image. The key characteristic of the pixel of maximum localization is that it is where the geometric image of the star is found at the start of the exposure of the frame under correction. The correction is performed in the form of frame processing with a digital finite-impulse-response (FIR) filter. The impulse response of the filter is inhomogeneous and represents a core of rotational blur, synthesized in each pixel of the corrected frame. Algorithms for calculating levels of the signal, background, and noise in the image of a star observed against the background of the daytime sky with a rotating camera are described. Dependences of the signal-to-noise ratios in various pixels of a blurred image on the exposure time and on the angular velocity of the camera rotation are analyzed. The signal-to-noise ratios in the star image before and after the blur correction are calculated. The simulation results are illustrated by the example of an image of a bright star, clearly showing specific features of the proposed rotational blur correction algorithm.

102-111

Authors: R.R. Diyazitdinov

In this article, we describe an iterative algorithm for accurate superposition of contours with non-uniform sampling step. The processing contours are characterized by the same shape, but the sampling step is non-uniform, with no matching between points of the superposed contours. This makes impossible the use of methods for estimating superposition parameters by matching points. The algorithm proposed herein allows estimating the offsets and rotation angle separately. The idea of the algorithm is to perform the iterative correction of parameters. An estimate of the offsets is used to estimate the rotation angle and, vice versa, an estimate of the rotation angle is used to estimate the offsets. The proposed algorithm is characterized by a higher speed of processing than a brute force algorithm and a lower estimation error than algorithms that analyze contour macroparameters.

118-125

Authors: I.V. Arinichev, S.V. Polyanskikh, I.V. Arinicheva

The paper explores the possibility of semantic segmentation of the yellow rust and wheat blotch classification using the U-Net convolutional neural network architecture. Based on an own dataset of 268 images, collected in natural conditions and in infectious nurseries of the Federal Research Center for Biological Plant Protection (VNII BZR), it is shown that the U-Net architecture with ResNet decoders is able to qualitatively detect, classify and localize rust and spotting even in cases where diseases are present on the plant at the same time. For individual classes of diseases, the main metrics (accuracy, micro-/macro precision, recall, and F1) range from 0.92 to 0.96. This indicates the possibility of recognizing even a few diseases on a leaf with an accuracy that is not inferior to that of a plant pathology expert. The IoU and Dice segmentation metrics are 0.71 and 0.88, respectively, which indicates a fairly high quality of pixel-by-pixel segmentation and is confirmed by visual analysis. The architecture of the neural network used in this case is quite lightweight, which makes it possible to use it on mobile devices without connecting to the network.

137-151

Authors: A. Uzhinskiy, K. Vergel

Atmospheric heavy metal contamination is a real threat to human health. In this work, we examined several models trained on in situ data and indices got from satellite images. During 2018-2019, 281 samples of naturally growing mosses were collected in the Vladimir, Yaroslavl, and Moscow regions in Russia. The samples were analyzed using Neutron Activation Analysis to get the contamination levels of 18 heavy metals. The Google Earth Engine platform was used to calculate indices from satellite images that represent summarized information about sampling sites. Statistical and neural models were trained on in situ data and the indices. We focused on the classification task with 8 levels of contamination and used balancing techniques to extend the training data. Three approaches were tested: variations of gradient boosting, multilayer perceptron, and Siamese networks. All these approaches produced results with minute differences, making it difficult to judge which one is better in terms of accuracy and graphical outputs. Promising results were shown for 9 heavy metals with an overall accuracy exceeding 89%. Al, Fe, and Sb contamination was predicted for 3,000 and 12,100 grid nodes on a 500 km2 area in the Central Russia region for 2019 and 2020. The results, methods, and perspectives of the adopted approach of using satellite data together with machine learning for HM contamination prediction are presented.

160-169

Authors: R.I. Abdulkadirov, P.A. Lyakhov

In this paper, we propose a natural gradient descent algorithm with momentum based on Dirichlet distributions to speed up the training of neural networks. This approach takes into account not only the direction of the gradients, but also the convexity of the minimized function, which significantly accelerates the process of searching for the extremes. Calculations of natural gradients based on Dirichlet distributions are presented, with the proposed approach introduced into an error backpropagation scheme. The results of image recognition and time series forecasting during the experiments show that the proposed approach gives higher accuracy and does not require a large number of iterations to minimize loss functions compared to the methods of stochastic gradient descent, adaptive moment estimation and adaptive parameter-wise diagonal quasi-Newton method for nonconvex stochastic optimization.

179-184

Authors: L.L. Chen

With the development of science and technology, agricultural production has been gradually industrialized, and the use of robots instead of humans for seeding is one of the agricultural industrializations. This paper studied the seeding path planning and path tracking algorithms of the seeding robot, carried out experiments, and compared the improved proportion, integral, differential (PID) algorithm with the traditional PID control algorithm. The results demonstrated that both the improved and non-improved control algorithms played a good role in tracking on the straight path, but the improved control algorithm had a better tracking effect on the turning path; the displacement deviation and angle deviation of the tracking trajectory of the improved PID algorithm were reduced faster and more stable than the traditional PID algorithm; the tracking trajectory was shorter and the operation time of the robot was less under the improved PID algorithm than the traditional one.