Underwater target detection with hyperspectral imagery for search and rescue missions

Date

2018-04-19

Author

Eken, Isa Cem
Çetin, Yasemin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

152
views

0
downloads

Fast and precise target detection is an issue in underwater object detection applications such as search and rescue missions. Hyperspectral imaging could be effective in determining different elements in a region thanks to its ability to provide detailed spectral information. Utilization of this rich spectral information calls for the analysis of spectral differences of objects on water surface (dry/wet) and underwater conditions. In our study, we investigated the effect of water column to the target spectrum with two water column correction models and evaluated the results obtained with these models in two detection algorithms. The results show that the methodology enhances underwater object detection performance. The materials used for the study are selected to be typical in search and rescue missions such as metal, cotton fabric with different colors and denim to evaluate the effect of these cases on the detectability of targets for such scenarios. © (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Subject Keywords

Hyperspectral, Underwater, Target detection, Search and rescue

URI

https://hdl.handle.net/11511/58022

DOI

https://doi.org/10.1117/12.2304637

Conference Name

24th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

Underwater target detection with hyperspectral imagery for search and rescue operations Eken, İsa Cem; Çetin, Yasemin; Department of Information Systems (2017) Fast and precise target detection is an issue in underwater object detection applications such as search and rescue, mine detection, archeological remains, etc. Hyperspectral imaging could be effective in determining different components in a selected region thanks to its ability to provide detailed spectral information. The detection of underwater objects with their above-water reflectance signature may not be efficient because of the reflectance changes due to water column. The detection should be conduct...
Absorbance Estimation and Gas Emissions Detection in Hyperspectral Imagery Başkurt, Nur Didem; Gur, Yusuf; Omruuzun, Fatih; Çetin, Yasemin (2016-05-19) Hyperspectral imaging in gas detection applications is a leading and widely studied research topic thanks to its high spectral resolution and remote detection ability. The main problems in these applications covers the leakage detection, gas identification, and quantification. The proposed algorithm aims to reach the transmittance and absorbance features of the gas and to detect the gaseous region by using the measured radiance data from the hyperspectral infrared sensors.
Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan (MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2015-9) Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment...
Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery Ergul, Mustafa; Sen, Nigar; Okman, O. Erman (2014-05-07) Anomaly detection (AD) is an important application for target detection in remotely sensed hyperspectral data. Therefore, variety kinds of methods with different advantages and drawbacks have been proposed for past two decades. Recently, the kernelized support vector data description (SVDD) based anomaly detection approaches has become popular as these methods avoid prior assumptions about the distribution of data and provides better generalization to characterize the background. The global SVDD needs a tra...
On Generalized Eigenvector Space For Target Detection in Reduced Dimensions Güvensen, Gökhan Muzaffer; Candan, Çağatay; Orguner, Umut (2015-05-15) The detection and estimation problems with large dimensional vectors frequently appear in the phased array radar systems equipped with, possibly, several hundreds of receiving elements. For such systems, a preprocessing stage reducing the large dimensional input to a manageable dimension is required. The present work shows that the subspace spanned by the generalized eigenvectors of signal and noise covariance matrices is the optimal subspace to this aim from several different viewpoints. Numerical results ...

Citation Formats

I. C. Eken and Y. Çetin, “Underwater target detection with hyperspectral imagery for search and rescue missions,” Orlando, FL, 2018, vol. 10644, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/58022.