Rolling Guidance Filtering-Orientated Saliency Region Extraction Method for Visible and Infrared Images Fusion

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jiangjiang Li ◽  
Lijuan Feng
2017 ◽  
Vol 54 (11) ◽  
pp. 111003
Author(s):  
许 磊 Xu Lei ◽  
崔光茫 Cui Guangmang ◽  
郑晨浦 Zheng Chenpu ◽  
赵巨峰 Zhao Jufeng

Author(s):  
Yuuki Yamasaki ◽  
Masahiro Migita ◽  
Go Koutaki ◽  
Masashi Toda ◽  
Tsuyoshi Kishigami

2013 ◽  
Vol 397-400 ◽  
pp. 2171-2176 ◽  
Author(s):  
Cong Ping Chen ◽  
Lei Zou ◽  
Wei Wang

By analyzing the gray level features of transition region, a new underwater image transition region extraction method based on Support Vector Machine (SVM) is presented. At first, a vector is constructed to fully describe the transition region, which includes local complexity, local difference and neighborhood homogeneity. Then, SVM is applied to train and classify the set of feature vectors, so that the transition region of the underwater image is extracted. Finally, the segmentation threshold is determined by mean of the histogram of the transition region, and the binary result was yielded. The experimental results show that the proposed algorithm can achieve a better transition region extraction and segmentation performance, and automatically select the optimal threshold for transition region extraction.


1986 ◽  
Vol 17 (5) ◽  
pp. 75-83
Author(s):  
Tomoharu Nagao ◽  
Takeshi Agui ◽  
Masayuki Nakajima

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