scholarly journals A Scale-Adaptive Matching Algorithm for Underwater Acoustic and Optical Images

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4226 ◽  
Author(s):  
Jun Liu ◽  
Benyuan Li ◽  
Wenxue Guan ◽  
Shenghua Gong ◽  
Jiaxin Liu ◽  
...  
Keyword(s):  
Estimation Method ◽  
Scale Space ◽  
Optical Data ◽  
Enhancement Effect ◽  
Underwater Acoustic ◽  
Iterative Processing ◽  
Similarity Estimation ◽  
Optical Images ◽  
Acoustic Images ◽  
Scale Detection

Underwater acoustic and optical data fusion has been developed in recent decades. Matching of underwater acoustic and optical images is a fundamental and critical problem in underwater exploration because it usually acts as the key step in many applications, such as target detection, ocean observation, and joint positioning. In this study, a method of matching the same underwater object in acoustic and optical images was designed, consisting of two steps. First, an enhancement step is used to enhance the images and ensure the accuracy of the matching results based on iterative processing and estimate similarity. The acoustic and optical images are first pre-processed with the aim of eliminating the influence of contrast degradation, contour blur, and image noise. A method for image enhancement was designed based on iterative processing. In addition, a new similarity estimation method for acoustic and optical images is also proposed to provide the enhancement effect. Second, a matching step is used to accurately find the corresponding object in the acoustic images that appears in the underwater optical images. In the matching process, a correlation filter is applied to determine the correlation for matching between images. Due to the differences of angle and imaging principle between underwater optical and acoustic images, there may be major differences of size between two images of the same object. In order to eliminate the effect of these differences, we introduce the Gaussian scale-space, which is fused with multi-scale detection to determine the matching results. Therefore, the algorithm is insensitive to scale differences. Extensive experiments demonstrate the effectiveness and accuracy of our proposed method in matching acoustic and optical images.

scholarly journals Robust Directional Angle Estimation of Underwater Acoustic Sources Using a Marine Vehicle

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3062 ◽  
Author(s):  
Jinwoo Choi ◽  
Jeonghong Park ◽  
Yoongeon Lee ◽  
Jongdae Jung ◽  
Hyun-Taek Choi
Keyword(s):  
Source Localization ◽  
Angular Displacement ◽  
Estimation Method ◽  
Time Delay Estimation ◽  
Accurate Estimation ◽  
Acoustic Source ◽  
Angle Estimation ◽  
Underwater Acoustic ◽  
Acoustic Sources ◽  
Marine Vehicle

Acoustic source localization is used in many underwater applications. Acquiring an accurate directional angle for an acoustic source is crucial for source localization. To achieve this purpose, this paper presents a method for directional angle estimation of underwater acoustic sources using a marine vehicle. It is assumed that the vehicle is equipped with two hydrophones and that the acoustic source transmits a specific signal repeatedly. The proposed method provides a probabilistic model for time delay estimation. The probability is recursively updated by prediction and update steps. The prediction step performs a probability transition using the angular displacement of the marine vehicle. The predicted probability is updated using a generalized cross correlation function with a verification process using entropy measurement. The proposed method can provide a reliable and accurate estimation of the directional angles of underwater acoustic sources. Experimental results demonstrate good performance of the proposed probabilistic directional angle estimation method in both an inland water environment and a harbor environment.

scholarly journals SAR AND OBLIQUE AERIAL OPTICAL IMAGE FUSION FOR URBAN AREA IMAGE SEGMENTATION

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 639-642 ◽  
Author(s):  
J. Fagir ◽  
A. Schubert ◽  
M. Frioud ◽  
D. Henke
Keyword(s):  
Image Segmentation ◽  
High Resolution ◽  
Single Channel ◽  
Research Area ◽  
Synthetic Aperture ◽  
Optical Data ◽  
Surface Model ◽  
Digital Surface Model ◽  
Oblique View ◽  
Optical Images

The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform – leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.

scholarly journals Underwater Acoustic Time Delay Estimation Based on Envelope Differences of Correlation Functions

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1259 ◽  
Author(s):  
Guodong Li ◽  
Jinsong Wu ◽  
Taolin Tang ◽  
Zhixin Chen ◽  
Jun Chen ◽  
...  
Keyword(s):  
Time Delay ◽  
Correlation Functions ◽  
Estimation Method ◽  
Digital Signal ◽  
Low Complexity ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Estimation Errors ◽  
Underwater Acoustic ◽  
Amplitude Fluctuations

This paper proposes underwater acoustic time delay estimation based on the envelope differences of correlation functions (EDCF), which mitigates the delay estimation errors introduced by the amplitude fluctuations of the correlation function envelopes in the traditional correlation methods (CM). The performance of the proposed delay estimation method under different time values was analyzed, and the optimal difference time values are given. To overcome the influences of digital signal sampling intervals on time delay estimation, a digital time delay estimation approach with low complexity and high accuracy is proposed. The performance of the proposed time delay estimation was analyzed in underwater multipath channels. Finally, the accuracy of the delay estimation using this proposed method was demonstrated by experiments.

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