scholarly journals Infrared small target detection algorithm based on spatial dissimilarity weighted local contrast

2021 ◽  
Author(s):  
Zhonghua Wang ◽  
Siwei Duan
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Local Contrast ◽  
Small Target ◽  
Small Target Detection ◽  
Infrared Small Target

scholarly journals Infrared Small Target Detection via Modified Random Walks

2018 ◽  
Vol 10 (12) ◽  
pp. 2004 ◽  
Author(s):  
Chaoqun Xia ◽  
Xiaorun Li ◽  
Liaoying Zhao
Keyword(s):  
Random Walks ◽  
Target Detection ◽  
Detection Algorithm ◽  
Local Contrast ◽  
Small Target ◽  
Global Uniqueness ◽  
Dimensional Image ◽  
Small Target Detection ◽  
Small Targets ◽  
Infrared Small Target

Infrared small target detection under intricate background and heavy noise is one of the crucial tasks in the field of remote sensing. Conventional algorithms can fail in detecting small targets due to the low signal-to-noise ratios of the images. To solve this problem, an effective infrared small target detection algorithm inspired by random walks is presented in this paper. The novelty of our contribution involves the combination of the local contrast feature and the global uniqueness of the small targets. Firstly, the original pixel-wise image is transformed into an multi-dimensional image with respect to the local contrast measure. Secondly, a reconstructed seeds selection map (SSM) is generated based on the multi-dimensional image. Then, an adaptive seeds selection method is proposed to automatically select the foreground seeds potentially placed in the areas of the small targets in the SSM. After that, a confidence map is constructed using a modified random walks (MRW) algorithm to represent the global uniqueness of the small targets. Finally, we segment the targets from the confidence map by utilizing an adaptive threshold. Extensive experimental evaluation results on a real test dataset demonstrate that our algorithm is superior to the state-of-the-art algorithms in both target enhancement and detection performance.

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