Investigation of image enhancement techniques for the development of a self-contained airborne radar navigation system

This study was devoted to an investigation of the feasibility of applying advanced image processing techniques to enhance radar image characteristics that are pertinent to the pilot's navigation and guidance task. Millimeter (95 GHz) wave radar images for the overwater (i.e., offshore oil rigs) and overland (Heliport) scenario were used as a data base. The purpose of the study was to determine the applicability of image enhancement and scene analysis algorithms to detect and improve target characteristics (i.e., manmade objects such as buildings, parking lots, cars, roads, helicopters, towers, landing pads, etc.) that would be helpful to the pilot in determining his own position/orientation with respect to the outside world and assist him in the navigation task. Results of this study show that significant improvements in the raw radar image may be obtained using two dimensional image processing algorithms. In the overwater case, it is possible to remove the ocean clutter by thresholding the image data, and furthermore to extract the target boundary as well as the tower and catwalk locations using noise cleaning (e.g., median filter) and edge detection (e.g., Sobel operator) algorithms

Real time sobel square edge detector for night vision analysis

Vision analysis with low or no illumination is gaining more and more attention recently, especially in the fields of security surveillance and medical diagnosis. In this paper, a real time sobel square edge detector is developed as a vision enhancer in order to render clear shapes of object in targeting scenes, allowing further analysis such as object or human detection, object or human tracking, human behavior recognition, and identification on abnormal scenes or activities. The method is optimized for real time applications and compared with existing edge detectors. Program codes are illustrated in the content and the results show that the proposed algorithm is promising to generate clear vision data with low noise

Spatiotemporal evolution of runaway electrons from synchrotron images in Alcator C-Mod

In the Alcator C-Mod tokamak, relativistic runaway electron (RE) generation can occur during the flattop current phase of low density, diverted plasma discharges. Due to the high toroidal magnetic field (B = 5.4 T), RE synchrotron radiation is measured by a wide-view camera in the visible wavelength range (~400-900 nm). In this paper, a statistical analysis of over one thousand camera images is performed to investigate the plasma conditions under which synchrotron emission is observed in C-Mod. In addition, the spatiotemporal evolution of REs during one particular discharge is explored in detail via a thorough analysis of the distortion-corrected synchrotron images. To accurately predict RE energies, the kinetic solver CODE [Landreman et al 2014 Comput. Phys. Commun. 185 847-855] is used to evolve the electron momentum-space distribution at six locations throughout the plasma: the magnetic axis and flux surfaces q = 1, 4/3, 3/2, 2, and 3. These results, along with the experimentally-measured magnetic topology and camera geometry, are input into the synthetic diagnostic SOFT [Hoppe et al 2018 Nucl. Fusion 58 026032] to simulate synchrotron emission and detection. Interesting spatial structure near the surface q = 2 is found to coincide with the onset of a locked mode and increased MHD activity. Furthermore, the RE density profile evolution is fit by comparing experimental to synthetic images, providing important insight into RE spatiotemporal dynamics

Estimating snow cover from publicly available images

In this paper we study the problem of estimating snow cover in mountainous regions, that is, the spatial extent of the earth surface covered by snow. We argue that publicly available visual content, in the form of user generated photographs and image feeds from outdoor webcams, can both be leveraged as additional measurement sources, complementing existing ground, satellite and airborne sensor data. To this end, we describe two content acquisition and processing pipelines that are tailored to such sources, addressing the specific challenges posed by each of them, e.g., identifying the mountain peaks, filtering out images taken in bad weather conditions, handling varying illumination conditions. The final outcome is summarized in a snow cover index, which indicates for a specific mountain and day of the year, the fraction of visible area covered by snow, possibly at different elevations. We created a manually labelled dataset to assess the accuracy of the image snow covered area estimation, achieving 90.0% precision at 91.1% recall. In addition, we show that seasonal trends related to air temperature are captured by the snow cover index.Comment: submitted to IEEE Transactions on Multimedi

Magnetic properties of nanoscale compass-Heisenberg planar clusters

We study a model of spins 1/2 on a square lattice, generalizing the quantum compass model via the addition of perturbing Heisenberg interactions between nearest neighbors, and investigate its phase diagram and magnetic excitations. This model has motivations both from the field of strongly correlated systems with orbital degeneracy and from that of solid-state based devices proposed for quantum computing. We find that the high degeneracy of ground states of the compass model is fragile and changes into twofold degenerate ground states for any finite amplitude of Heisenberg coupling. By computing the spin structure factors of finite clusters with Lanczos diagonalization, we evidence a rich variety of phases characterized by Z2 symmetry, that are either ferromagnetic, C-type antiferromagnetic, or of Neel type, and analyze the effects of quantum fluctuations on phase boundaries. In the ordered phases the anisotropy of compass interactions leads to a finite excitation gap to spin waves. We show that for small nanoscale clusters with large anisotropy gap the lowest excitations are column-flip excitations that emerge due to Heisenberg perturbations from the manifold of degenerate ground states of the compass model. We derive an effective one-dimensional XYZ model which faithfully reproduces the exact structure of these excited states and elucidates their microscopic origin. The low energy column-flip or compass-type excitations are robust against decoherence processes and are therefore well designed for storing information in quantum computing. We also point out that the dipolar interactions between nitrogen-vacancy centers forming a rectangular lattice in a diamond matrix may permit a solid-state realization of the anisotropic compass-Heisenberg model.Comment: 24 pages, 18 figure

Lane detection system for day vision using altera DE2

The active safety systems used in automotive field are largely exploiting lane detection technique for warning the vehicle drivers to correct any unintended road departure and to reach fully autonomous vehicles. Due to its ability, to be programmed, to perform complex mathematical functions and its characterization of high speed processing, Field Programmable Gate Array (FPGA) could cope with the requirement of lane detection implementation and application. In the present work, lane detection is implemented using FPGA for day vision. This necessitates utilization of image processing techniques like filtering, edge detection and thresholding. The lane detection is performed by firstly capturing the image from a video camera and converted to gray scale. Then, a noise filtering process for gray image is performed using Gaussian and average filter. Methods from first and second order edge detection techniques have been selected for the purpose of lane edge detection. The effect of manually changing the threshold level on image enhancement has been examined. The results showed that raising threshold level would better enhance the image. The type of FPGA device used in the present work is Altera DE2. Firstly, the version DE2 Cyclone II start with (11xxxxxx-xxxx) together with Genx camera has been used. This camera supports both formats NTSC and PAL, while the above version of FPGA backups only NTSC format. The software of lane detection is designed and coded using Verilog language