Real-time video mosaicking of the ocean floor

An approach was developed for real-time creation of video mosaics of the ocean floor. The approach uses visual correspondence during both image acquisition and consolidation to insure that there are no gaps in the mosaic. The use of visual information for mosaic creation offers an accuracy previously unachievable in real time. A complete mosaicking approach was developed, including a technique for image registration and several strategies for image acquisition control. The approach was implemented and tested experimentally. Ocean-floor mosaics were created in real time using a remotely-operated vehicle. In addition, extensive mosaicking experiments were conducted in a test-tank environment using a semiautonomous underwater robot     

Image registration for the underwater inspection using the maximum a posteriori technique

Describes an image registration method for underwater inspection tasks. A remotely operated vehicle equipped with a video camera and a scanning sonar is used as the testbed vehicle. Each image of the underwater scene is saved along with the video camera's position and orientation. The images are then combined to create a large composite picture of the underwater structure being inspected. This method is based upon a maximum a posteriori estimation technique and provides smooth and robust estimates of image shifts. Our results demonstrate the feasibility of this highly promising underwater inspection procedure.     

Large Area 3-D Reconstructions From Underwater Optical Surveys

Robotic underwater vehicles are regularly performing vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of detail and are easily interpreted by humans. Unfortunately, the coverage of a single image is limited by absorption and backscatter while what is generally desired is an overall view of the survey area. Recent works on underwater mosaics assume planar scenes and are applicable only to situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater robotic vehicle to form a 3-D reconstruction of the ocean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3-D structure) and scales to hundreds or thousands of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g., a compass, depth sensor, and a Doppler velocity log). Our approach is based on a combination of techniques from computer vision, photogrammetry, and robotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3-D submaps. These submaps are then placed in a common reference frame that is refined by matching overlapping submaps. The final stage of processing is a bundle adjustment that provides the 3-D structure, camera poses, and uncertainty estimates in a consistent reference frame. We present results with ground truth for structure as well as results from an oceanographic survey over a coral reef.      

3-D shape recovery of planar and curved surfaces from shading cuesin underwater images

Automatic construction of high-resolution topographical maps, or determining the shape of man-made objects, targets, and obstacles for localization, identification, and/or recognition, is an important capability in the application of autonomous or intelligent underwater vehicles. In this paper, we investigate the application of underwater image models for the reconstruction of three-dimensional object shapes from the shading cues in two-dimensional optical images. We first present the results of a sensitivity analysis in support of a simplified model for a Lambertian surface illuminated by a point source in an attenuating medium, proposed in earlier work. We then generalize a closed-form solution for planar scenes, previously proposed for negligible source-camera baseline, to the case where the baseline may be increased to minimize backscatter effects. For curved surfaces, we propose two techniques based on different iterative updating strategies to recursively improve the recovered surface shape. We study the performance of various methods using synthetic data and real images acquired under different turbidity conditions     

A detection model of underwater topography with a series of SAR images acquired at different time

underwater topography is one of oceanic features detected by Synthetic Aperture Radar. Underwater topography SAR imaging mechanism shows that tidal current is the important factor for underwater topography SAR imaging. Thus under the same wind field condition, SAR images for the same area acquired at different time include different information of the underwater topography. To utilize synchronously SAR images acquired at different time for the underwater topography SAR detection and improve the precision of detection, based on the detection model of underwater topography with single SAR image and the periodicity of tidal current, a detection model of underwater topography with a series of SAR images acquired at different time is developed by combing with tide and tidal current numerical simulation. To testify the feasibility of the presented model, Taiwan Shoal located at the south outlet of Taiwan Strait is selected as study area and three SAR images are used in the underwater topography detection. The detection results are compared with the field observation data of water depth carried out by R/V Dongfanghong 2, and the errors of the detection are compared with those of the single SAR image. All comparisons show that the detection model presented in the paper improves the precision of underwater topography SAR detection, and the presented model is feasible.     

海岛区域含云雾影像预处理技术研究

薄雾、朵云的影响导致光学遥感影像质量下降,欲有效开展海岛区域测绘需对相关影像进行必要的预处理。首先分析了海岛区域影像中薄雾和朵云的辐射及几何特点,其次采用改进的基于暗原色先验知识的薄雾处理方法和朵云及云影双阈值同时检测方法T多源影像配准后压盖地物信息替换,以及改进的影像匀光匀色方法。实验证明,上述方法能够有效地改善海岛区域影像的视觉质量,提高其作业效率。     

Underwater topography detection of Shuangzi Reefs with SAR images acquired in different time

1 IntroductionSynthetic aperture radar (SAR) is one of theadvanced microwave remote sensors of environmentand resource. It can observe targets in all weathersand all day and night in a multi-band, multi-polari-zation and multi-look angle mode. SAR has bee…     

海岛礁光学和雷达影像基于改进非子采样小波变换的自动配准

Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform （TSO-NSWT） for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 （multi-spectral） and YG-1 （SAR） images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error （RMSE） patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.     

水陆三维地形地貌融合应用研究

针对海量遥感数据和海洋测量数据的特点,采用Kriging插值算法和三角网构建高精度水下DEM数据,应用标准偏差算法和侧扫声纳镶嵌技术制作水下地貌影像,实现多元数据处理、融合和三维显示的技术流程.应用像素级数据融合技术实现海量水陆数据的连续、准确无缝拼接,解决海洋测绘信息空间一体化表达的技术难题.     

水下模糊图象维纳滤波和卡尔曼滤波恢复算法研究

该文将海水中图象传输特性的研究与用此传输特性进行水下模糊图象恢复结合起来 ,得到一套测量水体传递函数及进行水下图象处理的方法。采用维纳 (Wiener)滤波和卡尔曼 (Kalman)滤波算法 ,对模糊图象进了恢复。结果表明 ,利用计算机采用一定的算法对散射性质已知的水体造成的图象模糊可以进行有效的复原 ,且良好效果。     

基于水声环境空间中多模态深度融合模型的目标识别方法研究

随着对水下目标特性研究的深入和声学探测技术的发展,基于单模态的阵列式信息融合或基于空间信息的分布式信息融合的水下目标识别方法研究已有一定成果,但针对复杂海况导致单一物理场或单一融合层次的系统识别性能提高有限等方面影响的水下目标识别方法研究还有所不足,因此,开展基于多模态深度融合模型的水下目标识别方法研究可利用模态互补,共享信息而提升识别率。文中在国内外研究基础上,深入研究了基于到达时差法和多模态方法组合的检测方法,初步形成了基于水声环境空间中多模态深度融合模型的识别框架,开展了海洋中典型自然与人为事件的信号分析与特征提取,并在此基础上,设计新型基于海底基站的被动识别系统。该系统同步记录和由位置等组成的时间序列标记声、磁和压数据,可实现高精度、高分辨率的识别。本研究可满足未来海洋观测对高性能水下目标探测、定位和跟踪系统的迫切需要,为海洋安全监管、海洋突发事件应急响应等领域提供新的技术手段和科学参考。     

Mosaic-based navigation for autonomous underwater vehicles

We propose an approach for vision-based navigation of underwater robots that relies on the use of video mosaics of the sea bottom as environmental representations for navigation. We present a methodology for building high-quality video mosaics of the sea bottom in a fully automatic manner, which ensures global spatial coherency. During navigation, a set of efficient visual routines are used for the fast and accurate localization of the underwater vehicle with respect to the mosaic. These visual routines were developed taking into account the operating requirements of real-time position sensing, error bounding, and computational load. A visual servoing controller, based on the vehicle's kinematics, is used to drive the vehicle along a computed trajectory, specified in the mosaic, while maintaining constant altitude. The trajectory toward a goal point is generated online to avoid undefined areas in the mosaic. We have conducted a large set of sea trials, under realistic operating conditions. This paper demonstrates that without resorting to additional sensors, visual information can be used to create environment representations of the sea bottom (mosaics) and support long runs of navigation in a robust manner.     

Vision-based system of AUV for an underwater pipeline tracker

This paper describes a new framework for detection and tracking of underwater pipeline,which includes software system and hardware system.It is designed for vision system of AUV based on monocular CCD camera.First,the real-time data flow from image capture card is pre-processed and pipeline features are extracted for navigation.The region saturation degree is advanced to remove false edge point group after Sobel operation.An appropriate way is proposed to clear the disturbance around the peak point in the process of Hough transform.Second,the continuity of pipeline layout is taken into account to improve the efficiency of line extraction.Once the line information has been obtained,the reference zone is predicted by Kalman filter.It denotes the possible appearance position of the pipeline in the image.Kalman filter is used to estimate this position in next frame so that the information of pipeline of each frame can be known in advance.Results obtained on real optic vision data in tank experiment are displayed and discussed.They show that the proposed system can detect and track the underwater pipeline online,and is effective and feasible.     

基于非锐化掩模引导滤波的水下图像细节增强算法研究

针对水下图像对比度偏低,细节模糊的问题,本文提出基于非锐化掩模引导滤波的细节增强方法。首先由原始图像做引导图进行滤波得到细节层图像,并对细节层使用噪声检测的中值滤波去除斑点噪声;然后对原始图像进行基于均值滤波的非锐化掩模,得到锐化图像,并将锐化图像作为引导图对原始图像进行引导滤波,获取基础层图像;最后将滤波后的细节层进行增益后与引导滤波获取的基础层进行叠加,达到增强水下图像细节的目的。并通过信息熵、局部对比度和平均梯度3种客观评价指标对图像处理结果进行了对比分析,主观和客观测试结果表明,本文采用的算法能够有效提高图像对比度以及增强细节信息,有利于提高水下图像资料解释的准确性。     

Development of real-time acoustic image recognition system using by autonomous marine vehicle

Automation of complicated underwater tasks require acoustic image based object recognition. This paper presents an acoustic image based real-time object recognition system. We proposed an acoustic image predictor to estimate an object's shape in advance. Depending on the acoustic camera's position, the predictor generates optimal template for recognition. The proposed method is implemented in our autonomous marine vehicle. For real-time processing, efficient recognition strategies are addressed. The vehicle detects an object and localizes it for recognition. In the detection process, the acoustic image's specific characteristics are used as the detection cues. In the localization process, the vehicle's horizontal and vertical positioning strategies are described. Efficient template generation method to minimize computing power is addressed. This realizes real-time recognition using the vehicle. To estimate the proposed system's accuracy and reliability, a recognition test was carried out in the field. The vehicle successfully recognized two different objects with high accuracy.     

Model of an underwater imaging system with a complexly modulated illumination beam

The optical transfer functions of underwater imaging systems that use narrow beams modulated by a complex high-frequency signal to form an image are studied. Images of simple objects observed with the use of such systems are calculated. The image distortions caused by the interference of modulation waves are estimated, and a method for eliminating these distortions is proposed. The potential for improving the image quality through the application of complexly modulated illumination beams is demonstrated using explicit calculations.     

水下光学无线通信的海水信道特性研究

提出了将具有比声学高达几倍的数据通信速率,良好的安全性和隐蔽性的光学无线通信技术应用于海军、海洋科学研究和水下工程等领域,实现高速率的水下无线通信技术实现海量数据的信息交换.基于生物光学特性的水下光学信道模型,建立了水下光学通信系统性能分析方法.并对基于发光二极管(LED)的水下光学无线通信系统进行了仿真,其结果表明所建立的方法可以进行各种海域水质环境的模拟,便于时水下光学无线通信系统性能进行预测评估,为水下光学无线通信系统的设计方案的评估提供了依据.     

In Situ Alignment Calibration of Attitude and Doppler Sensors for Precision Underwater Vehicle Navigation: Theory and Experiment

This paper reports the development and experimental evaluation of two in situ least squares techniques for estimating the alignment matrix of Doppler sonars commonly used for precision navigation of oceanographic submersibles. Most previously reported methods addressed the problem of single degree-of-freedom heading alignment using bottom-lock Doppler sonar data and global positioning system (GPS) navigation data. This paper reports and evaluates two techniques for three degree-of-freedom calibration of attitude and Doppler sonar sensors using sensor data available to vehicles at full ocean depth. The first technique provides a general linear least squares estimate of the alignment matrix. The second technique results in a least squares alignment matrix estimate constrained to the group of rotation matrices. The performance of these estimates is evaluated with a laboratory remotely operated vehicle (ROV) and a field-deployed autonomous underwater vehicle (AUV). Experimental results are reported which demonstrate that Doppler navigation employing the reported alignment calibration techniques significantly improves navigation precision. The experiments show that the latter technique provides calibration estimates that improve Doppler navigation precision not only on the calibration data set itself, but also provide improved precision over a wide variety of vehicle trajectories other than the calibration data set.     

基于固有频率的海洋平台损伤检测方法的改进

针对海洋平台损伤检测方法中需要未损伤模型参数的不便,提出了一种相对频率变化量的方法。对不同类型构件的损伤及同一类型构件在不同位置损伤的情况,进行结构模态分析,研究平台结构的固有频率对损伤、损伤位置和损伤程度的敏感性,以及平台质量变化对频率的影响。利用两次测量的相对频率变化量,可以发现损伤的存在,并进行损伤的初步定位。