Small target detection using cross product based on temporal profile in infrared image sequences

2010 ◽  
Vol 36 (6) ◽  
pp. 1156-1164 ◽  
Author(s):  
Tae-Wuk Bae ◽  
Byoung-Ik Kim ◽  
Young-Choon Kim ◽  
Kyu-Ik Sohng
Keyword(s):  
Target Detection ◽  
Infrared Image ◽  
Cross Product ◽  
Image Sequences ◽  
Small Target ◽  
Temporal Profile ◽  
Small Target Detection

DETECTION OF MOVING SMALL TARGETS IN INFRARED IMAGE SEQUENCES CONTAINING CLOUD CLUTTER

2004 ◽  
Vol 18 (02) ◽  
pp. 247-260 ◽  
Author(s):  
WEI WU ◽  
JIAXIONG PENG
Keyword(s):  
Target Detection ◽  
Infrared Image ◽  
Spatial Filtering ◽  
Image Sequences ◽  
Small Target ◽  
Temporal Filtering ◽  
Small Target Detection ◽  
Small Targets ◽  
Novel Algorithm

Detecting and tracking dim moving small targets in infrared image sequences containing cloud clutter is an important area of research. The paper proposes a novel algorithm for the dim moving small target detection in cloudy background. The algorithm consists of three courses. The first course consists of the image spatial filtering and the sequence temporal filtering, it can be realized by two parallel calculative parts. The second course is the fusion and the segmentation processing. The last course is the targets acquiring and tracking, it can be achieved by the Kalman tracker. The results of our experiment prove that the algorithm is very effective.

Design of Dim-Small Target Detection on Infrared Image Based on NIOSⅡ

2012 ◽  
Vol 27 (6) ◽  
pp. 814-819
Author(s):  
穆治亚 MU Zhi-ya ◽  
魏仲慧 WEI Zhong-hui ◽  
何昕 HE Xin ◽  
梁国龙 LIANG Guo-long ◽  
林为才 LIN Wei-cai
Keyword(s):  
Target Detection ◽  
Infrared Image ◽  
Small Target ◽  
Small Target Detection

scholarly journals Flying Small Target Detection for Anti-UAV Based on a Gaussian Mixture Model in a Compressive Sensing Domain

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2168 ◽  
Author(s):  
Chuanyun Wang ◽  
Tian Wang ◽  
Ershen Wang ◽  
Enyan Sun ◽  
Zhen Luo
Keyword(s):  
Compressive Sensing ◽  
Target Detection ◽  
Sparse Matrix ◽  
Infrared Image ◽  
Matrix Decomposition ◽  
Gaussian Mixture ◽  
Visual Surveillance ◽  
Low Rank ◽  
Small Target ◽  
Small Target Detection

Addressing the problems of visual surveillance for anti-UAV, a new flying small target detection method is proposed based on Gaussian mixture background modeling in a compressive sensing domain and low-rank and sparse matrix decomposition of local image. First of all, images captured by stationary visual sensors are broken into patches and the candidate patches which perhaps contain targets are identified by using a Gaussian mixture background model in a compressive sensing domain. Subsequently, the candidate patches within a finite time period are separated into background images and target images by low-rank and sparse matrix decomposition. Finally, flying small target detection is achieved over separated target images by threshold segmentation. The experiment results using visible and infrared image sequences of flying UAV demonstrate that the proposed methods have effective detection performance and outperform the baseline methods in precision and recall evaluation.

Adaptive small target detection based on evaluating complex degree of infrared image

2009 ◽  
Author(s):  
Qing-yu Hou ◽  
Wei Zhang ◽  
Chun-feng Wu ◽  
Qiu-ming Li ◽  
Li-hong Lu ◽  
...  
Keyword(s):  
Target Detection ◽  
Infrared Image ◽  
Small Target ◽  
Small Target Detection

Infrared Small Target Detection Based on Morphology and SUSAN Algorithm

2019 ◽  
Vol 34 (06) ◽  
pp. 2050013 ◽  
Author(s):  
Zhiwei Hu ◽  
Yixin Su
Keyword(s):  
Target Detection ◽  
Infrared Image ◽  
Frequency Region ◽  
Guidance System ◽  
Background Suppression ◽  
Small Target ◽  
High Frequency Region ◽  
Small Target Detection ◽  
Small Targets ◽  
Infrared Small Target

Infrared small target detection is one of the key techniques in infrared imaging guidance system. The technology of infrared small target detection still needs to be further studied to improve the detection performance. This paper combines the high-pass filtering characteristics of morphological top-hat transform with SUSAN algorithm, and proposes a small infrared target detection method based on morphology and SUSAN algorithm. This method uses top-hat transform to detect the high-frequency region in infrared image, and filters out the low-frequency region in the image to implement the preliminary background suppression of infrared image. Then the SUSAN algorithm is used to detect small targets in the image after background suppression. The proposed method is applied to the single infrared image which is acquired by the infrared guidance system in the process of detecting and tracking the target under specific conditions. The experimental results show that the method is effective and can detect infrared small targets under different background.

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