DSP design for real-time hyperspectral target detection based on spatial-spectral information extraction

2012 ◽  
Author(s):  
Wei Yang ◽  
Bing Zhang ◽  
Lianru Gao ◽  
Yuanfeng Wu
Keyword(s):  
Information Extraction ◽  
Real Time ◽  
Target Detection ◽  
Spectral Information

scholarly journals Background Information Self-Learning Based Hyperspectral Target Detection

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Yufei Tian ◽  
Jihai Yang ◽  
Shijun Li ◽  
Wenning Xu
Keyword(s):  
Information Extraction ◽  
Hyperspectral Imaging ◽  
Target Detection ◽  
Detection Method ◽  
Experimental Results ◽  
Hyperspectral Images ◽  
Background Information ◽  
Spectral Information ◽  
Tumor Region ◽  
Self Learning

Hyperspectral imaging has been proved as an effective way to explore the useful information behind the land objects. And it can also be adopted for biologic information extraction, by which the origin information can be acquired from the image repeatedly without contamination. In this paper we proposed a target detection method based on background self-learning to extract the biologic information from the hyperspectral images. The conventional unstructured target detectors are very difficult to estimate the background statistics accurately in either a global or local way. Considering the spatial spectral information, its performance can be further improved by avoiding the above problem. It is especially designed to extract fingerprint and tumor region from hyperspectral biologic images. The experimental results show the validity and the superiority of our method on detecting the biologic information from hyperspectral images.

scholarly journals A COMPARATIVE ANALYSIS OF SPECTRAL INFORMATION EXTRACTION ALGORITHMS FOR TARGET DETECTION OF HYDROTHERMAL ALTERATION ZONES USING ASTER SATELLITE IMAGE DATA

2020 ◽  
Vol V-3-2020 ◽  
pp. 649-654
Author(s):  
A. J. Abubakar ◽  
M. Hashim ◽  
A. B. Pour ◽  
Y. Saleh
Keyword(s):  
Information Extraction ◽  
Target Detection ◽  
Hydrothermal Alteration ◽  
Satellite Image ◽  
Image Data ◽  
Spectral Information ◽  
Spectral Angle Mapper ◽  
Alteration Zones ◽  
Satellite Image Data ◽  
Hydrothermal Alteration Zones

Abstract. The focus of this paper is to evaluate the performance of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for target detection of hydrothermal alteration zones associated with geothermal (GT) springs as proxy for narrowing areas of interest. The study employed the Per-pixel Spectral Angle Mapper (SAM) and the Sub-pixel Linear Spectral Unmixing (LSU) algorithms for spectral information extraction by using the ASTER satellite image data. In both cases, image endmember spectra specifically for kaolinite, alunite, and illite and calcite zones were selected and extracted by using the Analytical Imaging and Geophysics (AIG)-developed processing methods. The results of the analysis show that both SAM and LSU discriminated targets of interest better when employing image spectra and poorly when using library spectra. However, the Per-pixel SAM is unsuitable for target detection and more suited where the objective of the investigation is to classify whole scene and not particular targets as in this case. The LSU was found to be effective for discriminating alterations associated with the thermal springs especially where image endmember spectra are employed for analysis, thus recommended for prefeasibility mapping of GT related resources.

scholarly journals Automatic Acoustic Target Detecting and Tracking on the Azimuth Recording Diagram with Image Processing Methods

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5391
Author(s):  
Fan Yin ◽  
Chao Li ◽  
Haibin Wang ◽  
Fan Yang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Target Detection ◽  
Ambient Noise ◽  
Arrival Direction ◽  
Processing Methods ◽  
Acoustic Target ◽  
Real Time Tracking ◽  
Passive Acoustic ◽  
Target Detecting

Passive acoustic target detection has been a hot research topic for a few decades. Azimuth recording diagram is one of the most promising techniques to estimate the arrival direction of the interested signal by visualizing the sound wave information. However, this method is challenged by the random ambient noise, resulting in low reliability and short effective distance. This paper presents a real-time postprocessing framework for passive acoustic target detection modalities by using a sonar array, in which image processing methods are used to automate the target detecting and tracking on the azimuth recording diagram. The simulation results demonstrate that the proposed approach can provide a higher reliability compared with the conventional ones, and is suitable for the constraints of real-time tracking.

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