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Underwater objects classifier based on super-resolution spatial spectrum variance

机译：基于超分辨率空间谱差异的水下对象分类器

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摘要

In underwater environment, the low speed target recognition has been a challenge problem. A design for underwater objects identification is suggested in this paper. The construction can be used in harbor surveillance and ocean environment inspection. Utilizing super-resolution beamforming, the distinctions between the low-speed object (such as buoy or low speed AUV) and the beacon can be observed in spatial-temporal spectrum. Corresponding to the features of power differences and spatial spectrum variance in vertical direction, the low-speed object can be separated from beacon. The data from lake experiment is dealt with and illustrate the method.

机译：在水下环境中，低速目标识别是一个挑战问题。本文提出了一种用于水下物体的设计。该建筑可用于海港监测和海洋环境检验。利用超分辨率波束成形，在空间频谱中可以观察到低速物体（例如浮标或低速AUV）和信标之间的区别。对应于功率差异的特征和垂直方向上的空间谱差异，低速物体可以与信标分开。处理来自湖泊实验的数据并说明了该方法。

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《OCEANS Conference》|2019年|779p|共4页
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Xuan Li; XiaoChuan Ma;
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正文语种
中图分类海洋工程;
关键词
Reverberation; Array signal processing; Target recognition; Synthetic aperture sonar; Sonar detection;

机译：混响;阵列信号处理;目标识别;合成孔径声纳;声纳检测;

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专利

1. A SPATIAL DOMAIN OBJECT SEPARABILITY BASED NO-REFERENCE IMAGE QUALITY MEASURE USING MEAN AND VARIANCE [J] . KANJAR DE, V. MASILAMANI International Journal of Image and Graphics . 2013,第2期

机译：基于均值和方差的基于空间域对象可比性的无参考图像质量测量
2. Object-oriented and pixel-based classification approaches to classify tropical successional stages using airborne high-spatial resolution images [J] . Piazza Gustavo Antonio, Vibrans Alexander Christian, Liesenberg Veraldo, GIScience & remote sensing . 2016,第2期

机译：面向对象和基于像素的分类方法，使用机载高空间分辨率图像对热带演替阶段进行分类
3. The Design of an Object-based System for Representing and Classifying Spatial Structures and Relations [J] . Florence Le Ber, Amedeo Napoli Journal of Universal Computer Science . 2002,第8期

机译：基于对象的空间结构和关系表示与分类系统的设计
4. Underwater objects classifier based on super-resolution spatial spectrum variance [C] . Xuan Li, XiaoChuan Ma OCEANS Conference . 2019

机译：基于超分辨率空间谱方差的水下物体分类器
5. Part based object detection, segmentation, and tracking by boosting simple shape feature based weak classifiers [D] . Wu, Bo 2008

机译：通过增强基于简单形状特征的弱分类器来进行基于零件的对象检测，分割和跟踪
6. Underwater Object Detection and Reconstruction Based on Active Single-Pixel Imaging and Super-Resolution Convolutional Neural Network [O] . Mengdi Li, Anumol Mathai, Stephen L. H. Lau, 2021

机译：基于主动单像素成像和超分辨率卷积神经网络的水下对象检测与重建
7. Classification performance assessment in side scan sonar image while underwater target object recognition using random forest classifier and support vector machine [O] . R Kumudham, V Rajendran, . . 2018

机译：使用随机林类分类器和支持向量机的水下目标对象识别时侧扫描声纳图像的分类性能评估
8. Multiple Window Based Minimum Variance Broadband Spatial Spectrum Estimation [R] . Liu, T. C., VanVeen, B. D. 1990

机译：基于多窗口的最小方差宽带空间谱估计

Underwater objects classifier based on super-resolution spatial spectrum variance

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