多波束声呐图像条带中央和边缘残差处理方法

多波束声呐图像是进行海底底质分类的主要数据源之一,由于受海洋噪声、声波散射和混响、仪器设备等因素影响,其经各项常规改正后仍存在明显残差,突出表现在中央波束区和条带重叠区,难以形成高质量的声呐图像。文中分析了多波束声呐图像残差的成因及影响,提出了一种基于多条带最小二乘拟合的多波束声呐图像残差处理方法。首先,得到相邻声脉冲(ping)信号中央区域、重叠区域以及整体趋势的拟合函数;然后,通过拟合函数计算得到中央和重叠区域的残差改正系数;最后,通过改正系数进行残差改正。实验分析表明,该方法在保留原始细节的基础上,有效削弱了残差对声呐图像的影响,对多波束声呐图像处理具有参考和应用价值。     

Fault scarp identification in side-scan sonar and bathymetry images from the Mid-Atlantic Ridge using wavelet-based digital filters

Digital filters designed using wavelet theory are applied to high resolution deep-towed side-scan sonar data from the median valley walls, crestal mountains, and flanks of the Mid-Atlantic Ridge at 29°10 N. With proper tuning, the digital filters are able to identify the location, orientation, length, and width of highly reflective linear features in sonar images. These features are presumed to represent the acoustic backscatter from axis-facing normal faults. The fault locations obtained from the digital filters are well correlated with visual geologic interpretation of the images. The side-scan sonar images are also compared with swath bathymetry from the same area. The digitally filtered bathymetry images contain nine of the eleven faults identified by eye in the detailed geologic interpretation of the side-scan data. Faults with widths (measured perpendicular to their strike) of less than about 150 m are missed in the bathymetry analysis due to the coarser resolution of these data. This digital image processing technique demonstrates the potential of wavelet-based analysis to reduce subjectivity and labor involved in mapping and analyzing topographic features in side-scan sonar and bathymetric image data.     

联合小波和NLM滤波的侧扫声纳回波信号降噪

为进一步降低侧扫声纳回波信号中非高斯分布的乘性噪声,获取更佳效果的侧扫声纳图像,提出了一种利用小波和NLM(nonlocal means)滤波的组合降噪方法.首先采用同态变换将侧扫声纳回波ping信号中的乘性噪声转换为加性噪声,然后利用小波阈值和NLM滤波对侧扫声纳每ping回波数据实施降噪处理,最后经过小波反变换和指...     

珊瑚环礁区侧扫声呐图像中的目标物识别方法

为研究西沙宣德环礁海底地貌特征及珊瑚分布情况,采用舷挂侧扫拖鱼的方式对环礁区域海底进行地貌扫测,从采集的侧扫声呐图像上可以识别出环礁区域珊瑚分布情况及珊瑚礁区地貌特征,利用侧扫声呐图像识别方法结合实物样品比对可以圈定出珊瑚分布范围、暗礁区域及环礁区域底质类型分布,采用基本的数学处理方法定量分析了水下珊瑚礁体的海底高度及疑似沉船的大小,分析了侧扫声呐图像显示的调查船转向效应。     

一种联合单波束测深的侧扫声呐海底线提取方法

论述了侧扫声呐的成像原理,针对目前常用侧扫声呐系统数据采集的相关特性,结合实际工程应用,提出了一种联合单波束测深的侧扫声呐海底线提取新方法,以便在数据后处理时进行快速准确地斜距改正。利用实测数据验证了该方法的有效性,并与成熟商用软件的提取结果和阈值法提取结果进行对比分析,结果表明该方法具有一定的可行性和优势。     

基于侧扫声纳图像海底目标物提取方法

分析了侧扫声纳数据成像原理,利用凹凸目标成像与阴影的关系,依次采用二值化处理、中值滤波处理、开启与闭合操作、Canny边缘提取等多种图像处理的手段,实现了海底目标物的提取与定位,并通过实验验证了本方法的可行性。     

基于粗集理论的声呐图像中值滤波

保边去噪是图像滤波中的主要问题。声呐图像像素少品质恶劣,保边去噪显得尤为重要。将基于粗集理论的中值滤波应用于声呐图像处理中,给出了实验结果。结果表明这种方法具有可行性。     

Spatial filtering for speckle reduction, contrast enhancement, andtexture analysis of GLORIA images

This paper reports a comparative study of digital enhancement techniques using spatial filtering to improve the geologic interpretation of side-scan sonar GLORIA images. Seven algorithms for speckle reduction with window sizes of 3×3-7×7 pixel and various numbers of iterations were tested for cosmetic purposes, and also to improve subsequent image processing. The filtered images were evaluated using both quantitative and qualitative techniques. It was determined that a normalized inverse gradient weighted smoothing scheme, with a 3×3 pixel filter and five iterations, allows a significant speckle reduction without blurring the edges in the GLORIA image which correspond to geological structures. Three local contrast enhancement techniques were also tested and evaluated to increase the perception of these geologic structures. Subtracting the gradient magnitude twice, calculated with spatial filters of a 5×5 pixel on smoothed images, was found to enhance most GLORIA images. Texture analysis methods developed for GLORIA images of mid-oceanic ridges and based on edge detection and orientation determination by spatial filtering are also presented. It enables the GLORIA mosaic of the Rodriguez triple junction (Indian Ocean) to be partitioned into regions of preferred orientation corresponding to the different seafloor fabrics generated at each arm of the triple junction     

The practical implementation of electronic stabilization for sectorscanning sonar displays

The natural motion of a ship at sea produces undesirable effects on sonar displays. To overcome this problem some form of stabilization is desirable. A practical sonar display system, which uses image processing techniques to stabilize the displayed sonar image against rotational motion is described. The stabilization method provides the capability of image enhancement as well as improved image interpretation due to an increased area of view and a geometrically correct conversion to polar display. Details of the three processing stages required in the system are provided. These processes are ship motion analysis, image integration, and polar display conversion. Stabilized results are given for simulated ship motion     

基于Kongsberg EM多波束的Snippet数据处理方法

多波束声呐记录的海底后向散射片段(Snippet)数据处理成角度响应曲线和地理编码(Mosaic)图像可以 帮助识别海底底质类型和反映地貌形态,这一过程包括辐射校正、角度响应改正(AVG)和几何地理编码,但不同的多波束系统硬件在辐射校正和角度响应改正方法上存在差异且传统处理方法忽略了声呐系统本身的指向性模型随时间变化的事实。以声呐方程为基础,针对Kongsberg EM 多波束系统提出了一套完整的Snippet数据处理流程,并分析了各步骤中存在的可变性,给出了每一步的处理建议,最后将此方法应用于EM2040浅水多波束实测数据,并验证了该方法的有效性和实用性。     

济州岛南部海域海底声呐图像分析与声学底质分类

东海北部外陆架靠近济州岛南部海域,是黄海槽向冲绳海槽延伸的部分,属于黑潮分支黄海暖流的通道入口,分布着脊槽相间的海底底形,对其海底声呐图像的处理分析及声学底质分类的分析研究,有助于了解该通道海底底形表层纹理特征及沉积物分布规律。基于在济州岛南部海域获取的多波束声呐数据,应用图像处理技术和方法,对数据进行了处理,获得了海底声呐影像图,并对其表层纹理特征进行了描述和分析;同时,基于多波束反向散射强度数据,结合19组海底地质取样数据,建立研究区海底反向散射强度与沉积物粒度特征之间的统计关系模型,并以改进的学习向量量化神经网络方法,实现对海底粉砂质砂、黏土质砂以及砂-粉砂-黏土3种底质类型的快速自动分类识别。     

两种多波束反向散射强度数据归一化方法的建立与分析

多波束反向散射强度数据应用广泛,但由于受到角度响应的影响,导致生成的多波束声呐图像质量偏低,且现有角度响应改正方法在复杂海底底质环境下适应性较差。为此本文对散射强度进行分析,给出了两种多波束反向散射强度数据归一化方法,分别为基于高斯拟合以及角度响应的散射强度改正方法,前者主要是基于散射强度的变化规律进行改正,而后者则是基于声波的散射机理进行改正。实验结果表明两种方法较传统改正方法精度均有约30%的提升,并且角度响应方法较高斯拟合方法改正精度更高,但计算效率有所下降。以上实验验证了两种方法的有效性,实现了散射强度数据的归一化,提升了多波束声呐图像的质量。     

小波函数对侧扫声纳图像滤波效果的影响分析

侧扫声纳技术应用日益广泛,已成为海洋测量的重要工具,而去除噪声处理是对侧扫声纳图像进行正确判读的前提。利用小波函数滤波处理的方法,分别采用Haar、Daubechies、Coiflets、Symlets、Discrete Meyer、Biorthogonal、Reverse Biorthogonal等小波函数与中值滤波函数对侧扫声纳图像进行处理,并以平滑指数和边缘保持指数为评价指标,对滤波效果进行定量比较。试验表明,小波函数可以有效地平滑声纳图像,并能保持其较好的边缘效果。     

混浊水域多波束反向散射强度传播损失改正

为了改善现有的反向散射强度传播损失改正方法在混浊水域适应性较弱的问题,提出了混浊水域声传播损失计算模型。首先利用不同深度的海洋环境参数构建声波吸收系数剖面,然后基于声速,沿波束传播路径,对每个波束分层计算传播损失。实验分析表明,本方法传播损失改正效果最佳,其Spearman等级相关系数绝对值仅为0.04,远小于传统模型和TVG改正,大大减弱了混浊水域情况下多波束回波强度与传播距离的相关性,有效改善了多波束声呐图像的质量。     

Dereverberation of marine reflection seismic data by a spatial combination of predictive deconvolution and velocity filtering

Contamination of seismic reflection records at early times by first-order water reverberations can be especially severe during survey operations over hard and flat sea floors on the continental shelf or in lake environments. A new dereverberation scheme based on two classical techniques — predictive deconvolution and velocity filtering — has been developed to address this problem. The techniques are combined spatially to take advantage of their complementary offset- and time-dependent properties. Stage I of the scheme consists of applying predictive deconvolution at short offset. The data are previously conditioned by a normal moveout correction with the water velocity which restores the periodicity of the reverberations in the offset-time plane and enhances the performance of deconvolution. Stage II of the scheme involves velocity filtering in the common-midpoint domain which is particularly effective at long offset where the moveout difference between primary reflections and reverberations is largest. The dereverberation scheme is well suited for the initial processing of large volumes of data due to the general availability of cost-effective deconvolution and velocity filtering algorithms in seismic processing software packages. Practical implementation issues are illustrated by a field example from the GLIMPCE survey in Lake Superior.Lithoprobe Publication No. 475.     

障碍物探测方法探讨

介绍了侧扫声纳、多波束测深系统、磁力仪的工作原理,提出了障碍物探测的相关技术要求。实例分析了综合利用侧扫声纳、多波束进行沉船探测的方法,结合侧扫声图和多波束水深探明障碍物的精确位置,测得最浅点水深,全面获得障碍物信息,大大提高了探测质量。对铁磁性小目标探测能力进行评估,并用实例加以分析和佐证。     

Technology for bottom relief and sedimentation surveys of White-Sea river estuaries

Experimental bottom relief survey technology and investigation results are presented. Investigations were conducted over about six years at several White-Sea river estuaries onboard the R/V Ecolog. Geomorphology data was obtained using an instrument complex that included an MKS, Microsound side scan sonar, AP-5 acoustic profiler, and LMS-350 echo sounder. ECHOGRAPH and WINRASTR original software was used for data gathering and processing.     

侧扫声纳图像增强技术

随着海洋探测技术的飞速发展,侧扫声纳的图像质量和定位精度迅速提高,其应用日益广泛和深入。在声纳图像判读分析时,常常需要进行辐射改正和均衡增强。根据海底地貌声纳图像的特点,归纳了几种有效、适用的图像增强方法,并建立了声纳图像分析软件。     

一种基于MATLAB的声呐条带图像自动拼接算法

准确地实现侧扫声呐条带的拼接对于了解海底地形、提高对海床地物反映的准确度起着重要的作用,而相邻条带的配准是声呐条带拼接的重要前提.MATLAB以其强大的矩阵运算功能及具有丰富的图像处理函数等特点,在图像处理方面占据明显的优势.文中利用MATLAB的IPT工具箱实现了基于互信息方法的声呐条带图像的自动快速配准,通过实验验证了该配准方法的有效性.并用小波变换方法对配准好的条带图像进行融合,实现声呐条带图像的有效拼接和镶嵌.