Computer Optics

319-324

Authors: S.Ya. Vetrov, A.Yu. Avdeeva, M.V. Pyatnov, I.V. Timofeev

Hybrid optical modes in a one-dimensional photonic crystal with a resonant nanocomposite defect bounded by a metallic layer are studied. The nanocomposite consists of spherical metallic constituents, that are distributed in a dielectric matrix. Transmittance, reflectance, and absorbance spectra of this structure, which is shined by light with normal incidence, are calculated. The possibility of control of the hybrid modes spectral characteristics by changing the thickness of the layer adjacent to the metal, the number of layers, and the nanocomposite filling factor is shown.

333-342

Authors: V.V. Kotlyar, A.G. Nalimov, A.A. Kovalev, A.P. Porfirev, S.S. Stafeev

We show here that in the sharp focus of a linearly polarized laser beam the spin vector flux has only transverse components (the effect of photonic wheels or photonic helicopter). For a linearly polarized optical vortex, the orbit-spin conversion leads to the appearance of both longitudinal and transverse components of the spin density vector in the focus. Spin-orbit conversion is experimentally demonstrated for a circularly polarized Gaussian beam when a transverse energy flux (orbital angular momentum) arises in the focus, which is transmitted to a microparticle and makes it rotate. Switching the handedness of circular polarization (from left to right) switches the microparticle rotation direction. It is also shown here that an azimuthally polarized vortex beam with an arbitrary integer topological charge generates in the focus a spin density vector that only has an axial component (pure magnetization), while the transverse spin flux is absent.

352-362

Authors: S.G. Volotovskiy, S.V. Karpeev, S.N. Khonina

In this paper, we consider a problem of reconstructing complex coefficients of the coherent superposition of Laguerre–Gaussian modes from the field intensity in a plane perpendicular to the propagation axis at a given distance using the Levenberg–Marquardt and Brent algorithm. The efficiency of using stage-by-stage optimization to restore complex coefficients of a superposition is demonstrated not only on model, but also on experimental intensity distributions. The algorithm can be used in optical information transmission through a turbulent atmosphere to process the received intensity distribution of the optical signal.

375-384

Authors: I.G. Zhurkin, L.N. Chaban, P.Yu. Orlov

When solving a variety of celestial navigation tasks there is a problem of determining parameters of spacecraft motion and onboard primary payload orientation based on the coordinates of registered star images. Furthermore, unwanted objects, like active satellites, natural and artificial space debris, that reduce the probability of correct recognition may get into the field of view of a satellite sensor. This prompts the necessity to filter out such interference from the star field images. However, if the objects under recognition are bodies located in near-Earth space, in this case, the star images themselves will act as interferences. In addition, since the detection and cataloging of these objects from the Earth’s surface is complicated by their small size, the atmospheric effects, as well as other technical difficulties, it is worthwhile to use the existing equipment onboard spacecrafts to solve this task. The existing recognition algorithms for star groups, as well as their classification, are presented in this paper. Moreover, a structurally topological approach for identifying groups of stars based on the properties of enveloping polygons used in constructing topological star patterns is proposed. Specific features in the construction of topological configurations on the analyzed set of points, as well as the principles of dynamic space object detection within their limits are described. Results of the numerical experiments performed using the developed algorithm on the star field maps and model scenes are presented.

393-400

Authors: Z.M. Gizatullin, S.A. Lyasheva, O.G. Morozov, M.P. Shleymovich

In this paper a new method for contour detection in grayscale images is proposed. The proposed method is based on the use of an image weight model, which allows one to estimate its pixels from the point of view of their significance for perception. In this case, the most significant pixels are those that contain characteristic features of the image, including brightness differences at the boundaries of the regions. To assess the significance of pixels, we propose a procedure for analyzing the contribution of the corresponding wavelet coefficients at different scale levels to the total energy of the image. The described method of contour detection involves building an image weight model, determining the directions of linear segments along the edges on the weight image, analyzing the significance of pixels and linking significant pixels. The advantage of the method is the high operation speed (the corresponding loop detector works on average four times faster than the Canny edge detector). In addition, the paper describes a detector of significant image areas, which is also based on the weight model. The proposed approach can be used in various systems of information processing and control based on methods and tools of computer vision, including control and navigation systems of unmanned vehicles, remote sensing of the Earth, systems for pavement defect detection, biometric systems, etc.

409-419

Authors: M.S. Boori, K. Choudhary, A.V. Kupriyanov

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.

427-435

Authors: A.A. Zakharov, D.V. Titov, A.L. Zhiznyakov, V.S. Titov

The paper discusses a method of visual attention based on vertex ranking of graphs on the basis of image features. The aim of the research is to develop a method that allows high-precision detection of objects in images with low color contrast between the selected and background areas. The image is pre-segmented into regions to calculate the saliency map. The graph is based on regions. Each region is associated with related regions, as well as with areas adjacent to adjacent regions. The regions are vertices of the graph. The vertices of the graph are ranked according to the characteristics of the corresponding image areas. The scope is highlighted based on requests from background areas. The saliency map is determined based on background area queries. Regions adjacent to the edges of the image belong to the background areas. Color features of the image were used in the existing approach of visual attention based on the manifold ranking. Texture features and shape features are additionally used in the proposed method to improve accuracy. Gabor's energy function is used to calculate texture features. The distance between centers of the regions is calculated by analyzing the form. The proposed method has shown good results for detecting objects in images in which the background color and object color are in similar ranges. The experimental results are presented on test images. Precision-recall curves showing the advantage of the developed method are constructed.

441-445

Authors: R.A. Paringer, Y. Donon, A.V. Kupriyanov

The article proposes a modification of the Blurred Image Matching (BIM) method, a key point selection method in images, thus solving a problem of their accurate comparison. A new approach for blobs selection and comparison is proposed. The use of these modifications allows us to achieve an increase in the proportion of correctly matched pairs of images by 30.2% compared to the basic method when working with noisy data.

454-465

Authors: V.A. Ermolaev, Y.A. Kropotov, A.Y. Proskuryakov

In this paper questions of building models of information exchange systems with discrete and distributed delay and with delayed feedback by methods of the theory of linear functional differential equations are investigated. When solving the said equations, it is necessary to consider restrictions caused by the uncertainties in the system under modeling, such as the absence of the exact data on the parameters of the model elements, their natural spread and temporal variations, thus requiring the solution of an identification problem. The models with continuous aftereffect introduced in this work take a fuller account of reflected signal characteristics in closed space, which increases the reliability of modeling results in comparison with the known differential models. At the same time, there is a problem of finding functions that characterize the value distribution of the echo delay. In this work, these functions (kernels) are approximated by a number of exponents, which simplifies the equations and allows the assumption that the aftereffect can be concentrated on both final and infinite intervals. The echo components caused by closed-space resonances are modeled by transfer functions of the corresponding linear links. In numerical modeling, a singlechannel model represented by a second-order resonance link and a pulse-shaped kernel described by a sum of two decreasing exponents is considered. The analysis of stability of the models of systems with delayed feedback is conducted by a frequency method. In the paper an approach to estimating the correlation and spectral functions of signals and noise components based on the parametric representation of the latter is considered. The paper also considers issues relating to the practical significance of the research results.

476-481

Authors: R.A. Shatalin, V.R. Fidelman, P.E. Ovchinnikov

In this paper, we propose an incremental learning scheme for the abnormal behavior detection algorithm based on principal component. The results obtained on a UCSD dataset and our experimental videos at a different number of training samples show that error rates are similar to conventional learning. Moreover, the proposed scheme allows the incremental learning time to be significantly reduced in comparison with a method based on matrix eigendecomposition.