Fusion of infrared and visible images through multi-level co-occurrence filtering

Wei Tan; Yizhong Liu

doi:10.1117/12.2579935

8 November 2020 Fusion of infrared and visible images through multi-level co-occurrence filtering

Wei Tan, Yizhong Liu

Proceedings Volume 11525, SPIE Future Sensing Technologies; 1152522 (2020) https://doi.org/10.1117/12.2579935
Event: SPIE Future Sensing Technologies, 2020, Online Only

Conference Poster

Abstract

Infrared and visible image fusion aims to obtain an integrated image which contains more recognizable in- formation. To attain this object, an effective infrared and visible image fusion algorithm through multi-level co-occurrence filtering is proposed in this paper. Firstly, the input images are decomposed into three layers through a co-occurrence filtering decomposition model. Secondly, a gradient-domain-based pulse-coupled neural network (PCNN) fusion strategy is applied in the three layers. Finally, the fused image is reconstructed by the three fused layers. Experiments show that the proposed algorithm outperform most state-of-the-art algorithms in both qualitative and quantitative measures.

Conference Presentation

Citation Download Citation

Wei Tan and Yizhong Liu "Fusion of infrared and visible images through multi-level co-occurrence filtering", Proc. SPIE 11525, SPIE Future Sensing Technologies, 1152522 (8 November 2020); https://doi.org/10.1117/12.2579935

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