scholarly journals Obtaining High-Resolution Seabed Topography and Surface Details by Co-Registration of Side-Scan Sonar and Multibeam Echo Sounder Images

2019 ◽  
Vol 11 (12) ◽  
pp. 1496 ◽  
Author(s):  
Shang ◽  
Zhao ◽  
Zhang
Keyword(s):  
High Resolution ◽  
Template Matching ◽  
High Accuracy ◽  
Transformation Model ◽  
Base Line ◽  
Initial Image ◽  
Side Scan Sonar ◽  
Speeded Up Robust Features ◽  
Seabed Topography ◽  
Echo Sounder

Side-scan sonar (SSS) is used for obtaining high-resolution seabed images, but with low position accuracy without using the Ultra Short Base Line (USBL) or Short Base Line (SBL). Multibeam echo sounder (MBES), which can simultaneously obtain high-accuracy seabed topography as well as seabed images with low resolution in deep water. Based on the complementarity of SSS and MBES data, this paper proposes a new method for acquiring high-resolution seabed topography and surface details that are difficult to obtain using MBES or SSS alone. Firstly, according to the common seabed features presented in both images, the Speeded-Up Robust Features (SURF) algorithm, with the constraint of image geographic coordinates, is adopted for initial image matching. Secondly, to further improve the matching performance, a template matching strategy using the dense local self-similarity (DLSS) descriptor is adopted according to the self-similarities within these two images. Next, the random sample consensus (RANSAC) algorithm is used for removing the mismatches and the SSS backscatter image geographic coordinates are rectified by the transformation model established based on the correct matched points. Finally, the superimposition of this rectified SSS backscatter image on MBES seabed topography is performed and the high-resolution and high-accuracy seabed topography and surface details can be obtained.

scholarly journals Obtaining 3D High-Resolution Underwater Acoustic Images by Synthesizing Virtual Aperture on the 2D Transducer Array of Multibeam Echo Sounder

2019 ◽  
Vol 11 (22) ◽  
pp. 2615 ◽  
Author(s):  
Bo Wei ◽  
Haisen Li ◽  
Tian Zhou ◽  
Siyu Xing
Keyword(s):  
High Resolution ◽  
Detection Efficiency ◽  
Processing Scheme ◽  
Transducer Array ◽  
Underwater Acoustic ◽  
Seabed Topography ◽  
Working Parameters ◽  
Imaging Algorithms ◽  
Along Track ◽  
Echo Sounder

In recent decades, imaging sonar has been the most widely employed remote sensing instruments in the field of underwater detection. The multibeam echo sounder (MBES) plays an important role in obtaining high-accuracy seabed topography. However, the resolution of the MBES substantially decreases with the increasing distance. Synthetic aperture sonar (SAS) achieves constant resolution on the along-track, improving the fineness of the image. However, conventional side-scan SAS usually only achieves 2D images, and gaps always exist. In this modeling and experimental research paper, we propose a novel underwater acoustic imaging scheme to improve the imaging performance of MBES, based on the complementarity of MBES and SAS systems. We design a 2D transducer array to increase the detection efficiency and obtain spatial gain. Moreover, the processing scheme is analyzed to design the working parameters in actual engineering applications. We exploit a target echo simulation approach to establish the research basics of the imaging algorithms, which also reflects the shapes and shadows of targets to match actual situations as realistically as possible. The proposed imaging algorithm synthesizes a virtual aperture receiving array on the along-track and reserves the multi-element manifold on the across-track. This helps to improve the imaging quality of the MBES and achieves high-resolution 3D detection with no gaps. Simulation and tank experimental results demonstrate that the proposed scheme can significantly improve the detection ability of the MBES, especially for small 3D target detection, thus making it suitable for 3D high-resolution underwater detection applications.

Terahertz frequency comb by multifrequency-heterodyning photoconductive detection for high-accuracy, high-resolution terahertz spectroscopy

2006 ◽  
Vol 88 (24) ◽  
pp. 241104 ◽  
Author(s):  
Takeshi Yasui ◽  
Yasuhiro Kabetani ◽  
Eisuke Saneyoshi ◽  
Shuko Yokoyama ◽  
Tsutomu Araki
Keyword(s):  
High Resolution ◽  
Terahertz Spectroscopy ◽  
Frequency Comb ◽  
High Accuracy ◽  
Terahertz Frequency

scholarly journals AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 651-654 ◽  
Author(s):  
Y. Xiang ◽  
W. Kang ◽  
F. Wang ◽  
H. You
Keyword(s):  
High Resolution ◽  
Urban Areas ◽  
Structural Information ◽  
Transformation Model ◽  
Reference Image ◽  
Building Detection ◽  
Phase Congruency ◽  
Sar Images ◽  
Local Variance ◽  
Complex Structural

Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

A 3D Optimized Frequency–Wavenumber (FK), Time–Space Optimized Symplectic (TSOS) Hybrid Method for Teleseismic Wave Modeling

2021 ◽  
Author(s):  
Weijuan Meng ◽  
Dinghui Yang ◽  
Xingpeng Dong ◽  
Jian Ma
Keyword(s):  
High Resolution ◽  
Seismic Wave ◽  
Hybrid Method ◽  
High Efficiency ◽  
Reference Model ◽  
3D Models ◽  
Realistic Model ◽  
High Accuracy ◽  
Memory Requirement ◽  
Time Space

ABSTRACT Although teleseismic waveform tomography can provide high-resolution images of the deep mantle, it is still unrealistic to numerically simulate the whole domain of seismic wave propagation due to the huge amount of computation. In this article, we develop a new three-dimensional hybrid method to address this issue, which couples the modified frequency–wavenumber (FK) method with the 3D time–space optimized symplectic (TSOS) method. First, the FK method, which is used to calculate the semianalytical incident wavefields in the layered reference model, is modified to compute the wavefields efficiently with a significantly low-memory requirement. Second, 3D TSOS method is developed to model the seismic wave propagating in the local 3D heterogeneous domain. The low memory requirement of the modified FK method and the high accuracy of the TSOS method make it feasible to obtain highly accurate synthetic seismograms efficiently. A crust–upper mantle model for P-, SV-, and SH-wave incidences is calculated to benchmark the accuracy and efficiency of the 3D optimized FK-TSOS method. Numerical experiments for 3D models with heterogeneities, undulated discontinuous interfaces, and realistic model in eastern Tibet, illustrate the capability of hybrid method to accurately capture the scattered waves caused by heterogeneities in 3D medium. The 3D optimized FK-TSOS method developed shows low-memory requirement, high accuracy, and high efficiency, which makes it be a promising forward method to further apply to high-resolution mantle structure images beneath seismic array.

scholarly journals Automated Georectification and Mosaicking of UAV-Based Hyperspectral Imagery from Push-Broom Sensors

2019 ◽  
Vol 12 (1) ◽  
pp. 34 ◽  
Author(s):  
Yoseline Angel ◽  
Darren Turner ◽  
Stephen Parkes ◽  
Yoann Malbeteau ◽  
Arko Lucieer ◽  
...  
Keyword(s):  
Transformation Model ◽  
Geometric Transformation ◽  
Motion Sensors ◽  
Computing Environment ◽  
Additional Time ◽  
Positional Accuracy ◽  
Speeded Up Robust Features ◽  
Ground Control Points ◽  
Fast Processing ◽  
Statistical Metrics

Hyperspectral systems integrated on unmanned aerial vehicles (UAV) provide unique opportunities to conduct high-resolution multitemporal spectral analysis for diverse applications. However, additional time-consuming rectification efforts in postprocessing are routinely required, since geometric distortions can be introduced due to UAV movements during flight, even if navigation/motion sensors are used to track the position of each scan. Part of the challenge in obtaining high-quality imagery relates to the lack of a fast processing workflow that can retrieve geometrically accurate mosaics while optimizing the ground data collection efforts. To address this problem, we explored a computationally robust automated georectification and mosaicking methodology. It operates effectively in a parallel computing environment and evaluates results against a number of high-spatial-resolution datasets (mm to cm resolution) collected using a push-broom sensor and an associated RGB frame-based camera. The methodology estimates the luminance of the hyperspectral swaths and coregisters these against a luminance RGB-based orthophoto. The procedure includes an improved coregistration strategy by integrating the Speeded-Up Robust Features (SURF) algorithm, with the Maximum Likelihood Estimator Sample Consensus (MLESAC) approach. SURF identifies common features between each swath and the RGB-orthomosaic, while MLESAC fits the best geometric transformation model to the retrieved matches. Individual scanlines are then geometrically transformed and merged into a single spatially continuous mosaic reaching high positional accuracies only with a few number of ground control points (GCPs). The capacity of the workflow to achieve high spatial accuracy was demonstrated by examining statistical metrics such as RMSE, MAE, and the relative positional accuracy at 95% confidence level. Comparison against a user-generated georectification demonstrates that the automated approach speeds up the coregistration process by 85%.

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