Title | ||
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A Novel Infrared and Visible Image Information Fusion Method Based on Phase Congruency and Image Entropy |
Abstract | ||
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In multi-modality image fusion, source image decomposition, such as multi-scale transform (MST), is a necessary step and also widely used. However, when MST is directly used to decompose source images into high- and low-frequency components, the corresponding decomposed components are not precise enough for the following infrared-visible fusion operations. This paper proposes a non-subsampled contourlet transform (NSCT) based decomposition method for image fusion, by which source images are decomposed to obtain corresponding high- and low-frequency sub-bands. Unlike MST, the obtained high-frequency sub-bands have different decomposition layers, and each layer contains different information. In order to obtain a more informative fused high-frequency component, maximum absolute value and pulse coupled neural network (PCNN) fusion rules are applied to different sub-bands of high-frequency components. Activity measures, such as phase congruency (PC), local measure of sharpness change (LSCM), and local signal strength (LSS), are designed to enhance the detailed features of fused low-frequency components. The fused high- and low-frequency components are integrated to form a fused image. The experiment results show that the fused images obtained by the proposed method achieve good performance in clarity, contrast, and image information entropy. |
Year | DOI | Venue |
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2019 | 10.3390/e21121135 | ENTROPY |
Keywords | Field | DocType |
image fusion,image entropy,PCNN,infrared and visible fusion,image decomposition,phase congruency | Mathematical optimization,Pattern recognition,Image fusion,Fusion,Fusion rules,Decomposition method (constraint satisfaction),Artificial intelligence,Artificial neural network,Phase congruency,Entropy (information theory),Mathematics,Contourlet | Journal |
Volume | Issue | Citations |
21 | 12 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xinghua Huang | 1 | 1 | 0.35 |
Guanqiu Qi | 2 | 164 | 16.20 |
Hongyan Wei | 3 | 1 | 0.35 |
Yi Chai | 4 | 1 | 0.35 |
Jaesung Sim | 5 | 2 | 0.70 |