Image Fusion Based on Residual Learning and Visual Saliency Mapping

Luoyi Ding; Jin Duan; Yu Song; Yong Zhu; Xiaoshan Yang

doi:10.3788/LOP57.161008

[1] Ben Hamza A, He Y, Krim H et al. A multiscale approach to pixel-level image fusion[J]. Integrated Computer-Aided Engineering, 12, 135-146(2005).

[2] Shao Z F, Liu J, Cheng Q M. Fusion of infrared and visible images based on focus measure operators in the curvelet domain[J]. Applied Optics, 51, 1910-1921(2012).

[3] Yang S Y, Wang M, Jiao L C et al. Image fusion based on a new contourlet packet[J]. Information Fusion, 11, 78-84(2010).

[4] Wang L, Li B, Tian L F. EGGDD: an explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain[J]. Information Fusion, 19, 29-37(2014).

[5] Zhou Z Q, Wang B, Li S et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters[J]. Information Fusion, 30, 15-26(2016).

[6] Zong J J, Qiu T S. Medical image fusion based on sparse representation of classified image patches[J]. Biomedical Signal Processing and Control, 34, 195-205(2017).

[7] Yu J Q, Duan J. Chen W M, at al. Underwater polarization image fusion based on NSST and adaptive SPCNN[J]. Laser & Optoelectronics Progress, 57, 061006(2020).

[8] Liu Y, Chen X, Peng H et al. Multi-focus image fusion with a deep convolutional neural network[J]. Information Fusion, 36, 191-207(2017).

[9] Li H, Wu X J, Kittler J. Infrared and visible image fusion using a deep learning framework. [C]∥2018 24th International Conference on Pattern Recognition (ICPR), August 20-24, 2018, Beijing, China. New York: IEEE, 2705-2710(2018).

[10] Zhou Z Q, Dong M J, Xie X Z et al. Fusion of infrared and visible images for night-vision context enhancement[J]. Applied Optics, 55, 6480-6490(2016).

[11] He K M, Sun J, Tang X O. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 1397-1409(2013).

[12] Ma J L, Zhou Z Q, Wang B et al. Infrared and visible image fusion based on visual saliency map and weighted least square optimization[J]. Infrared Physics & Technology, 82, 8-17(2017).

[13] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

[14] Shreyamsha Kumar B K. Image fusion based on pixel significance using cross bilateral filter[J]. Signal, Image and Video Processing, 9, 1193-1204(2015).

[15] Zhang Q, Fu Y, Li H et al. Dictionary learning method for joint sparse representation-based image fusion[J]. Optical Engineering, 52, 057006(2013).

[16] Liu C H, Qi Y, Ding W R. Infrared and visible image fusion method based on saliency detection in sparse domain[J]. Infrared Physics & Technology, 83, 94-102(2017).

[17] Liu Y, Chen X, Ward R K et al. Image fusion with convolutional sparse representation[J]. IEEE Signal Processing Letters, 23, 1882-1886(2016).

[18] Haghighat M, Razian M A. Fast-FMI: non-reference image fusion metric. [C]∥2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT), October 15-17, 2014, Astana, Kazakhstan. New York: IEEE, 1-3(2014).

[19] Shreyamsha Kumar B K. Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform[J]. Signal, Image and Video Processing, 7, 1125-1143(2013).