Multiple image processing to enhance stationary target detection

1992 ◽  
Author(s):  
Michael B. Sechtin ◽  
Michael C. Burl
Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5391
Author(s):  
Fan Yin ◽  
Chao Li ◽  
Haibin Wang ◽  
Fan Yang

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.


Hyperspectral image contains more information which are gathered from numerous narrow wavebands from one or more regions, and large amount of data are huddled. An basic problems in hyperspectral image processing are dimension reduction, target detection, target identification, and target classification. In this document, we reviewed the latest activities of target classification, most frequently used techniques for dimension reduction, target detection. Hyperspectral image processing is a complicated process which rely on mixed agents. Here we also recognized and reviewed problems faced by some methods and to overcome the problems, current techniques are discussed and highlighted good methods. To improving correctness, genuine classification techniques and Detection Techniques analysis are recommended


Author(s):  
Hui Yin ◽  
Jianping Peng ◽  
Wenwei Song ◽  
Xiaorong Gao ◽  
Jianqiang Guo ◽  
...  

2014 ◽  
Vol 1003 ◽  
pp. 216-220 ◽  
Author(s):  
Qi Li ◽  
Yu Yang ◽  
Zhong Ke Li ◽  
Jing Lu

According to the unmanned aerial vehicles real-time video image acquiring and target detection requirements, an image processing system was designed based on FPGA and TVP5150A decoder, and the video decoding hardware and software was also designed to meet the demands of unmanned aerial vehicles. An I2C controller was realized to assure the implementation of video decoding process in accordance with the requirements, and an image processing algorithm and applied to the image recognition process. Both of these were completed in FPGA using verilog HDL language. The correction of this image processing system was verified through real-time experiments.


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