Infrared Technology, Volume. 46, Issue 8, 902(2024)
Infrared and Visible Image Fusion Based on Global Energy Features and Improved PCNN
[1] [1] GONG J, WANG B, LIN Q, et al. Image fusion method based on improved NSCT transform and PCNN model[C]// 2016 9th International Symposium on Computational Intelligence and Design (ISCID) of IEEE, 2016, 1: 28-31.
[2] [2] LI J, LI B, JIANG Y. An infrared and visible image fusion algorithm based on LSWT-NSST[J]. IEEE Access, 2020, 8: 179857-179880.
[5] [5] YU Z A, YU L B, PENG S C, et al. IFCNN: a general image fusion framework based on convolutional neural network[J]. Information Fusion, 2020, 54: 99-118.
[6] [6] YU Z, BAI X, TAO W. Boundary finding based multi-focus image fusion through multi-scale morphological focus-measure[J]. Information Fusion, 2017, 35: 81-101.
[7] [7] MA J, WEI Y , LIANG P, et al. Fusion GAN: a generative adversarial network for infrared and visible image fusion[J]. Information Fusion, 2019, 48: 11-26.
[8] [8] ZHAO Z, XU S, ZHANG C, et al. DIDFuse: deep image decomposition for infrared and visible image fusion[EB/OL] [2020]. https:// ar5iv. labs.arxiv.org/html/2003.09210.
[9] [9] Nencini F, Garzelli A, Baronti S, et al. Remote sensing image fusion using the curvelet transform[J]. Information Fusion, 2007, 8(2): 143-156.
[10] [10] YANG S, MIN W, JIAO L, et al. Image fusion based on a new contourlet packet[J]. Information Fusion, 2010, 11(2): 78-84.
[13] [13] LI S, KANG X, FANG L, et al. Pixel-level image fusion: a survey of the state of the art[J]. Information Fusion, 2017, 33: 100-112.
[14] [14] Johnson J L. Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images[J]. Applied Optics, 1994, 33(26): 6239-6253.
[15] [15] Eckhorn R, Reitboeck H, Arndt M, et al. Feature linking via synchronization among distributed assemblies: simulations of results from cat visual cortex[J]. Neural Computation, 2014, 2(3): 293-307.
[16] [16] YIN M, LIU X, LIU Y, et al. Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain[J]. IEEE Transactions on Instrumentation and Measurement, 2018, 68(1): 49-64.
[20] [20] HE K, JIAN S, Fellow, et al. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2011, 33(12): 2341-2353.
[22] [22] Ganasala P, Prasad A D. Functional and Anatomical Image Fusion based on Texture Energy Measures in NSST Domain[C]// 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T) of IEEE, 2020: 417-420.
[23] [23] YU X, REN J, CHEN Q, et al. A false color image fusion method based on multi-resolution color transfer in normalization YCBCR space[J]. Optik-International Journal for Light and Electron Optics, 2014, 125(20): 6010-6016.
[24] [24] CHEN Y, Park S K, MA Y, et al. A new automatic parameter setting method of a simplified PCNN for image segmentation[J]. IEEE Transactions on Neural Networks, 2011, 22(6): 880-892.
[25] [25] Toet A, Franken E M. Perceptual evaluation of different image fusion schemes[J]. Displays, 2003, 24(1): 25-37.
[26] [26] LIU Y, LIU S, WANG Z. A general framework for image fusion based on multi-scale transform and sparse representation[J]. Information Fusion, 2015, 24: 147-164.
[27] [27] LI H, WU X J. Infrared and visible image fusion using latent low-rank representation[J/OL]. arXiv preprint arXiv:1804.08992, 2018.
[28] [28] Kumar B. Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform[J]. Signal, Image & Video Processing, 2013, 7: 1125-1143.
[29] [29] ZHOU Z, BO W, SUN L, et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters[J]. Information Fusion, 2016, 30: 15-26.
[30] [30] Alexander T. TNO Image Fusion Dataset[EB/OL]. [2014-04-26]. https:// www.semanticscholar.org/paper/TNO-Image-Fusion-Dataset-Alexander/ fcdfecf97c55db0a431788d01e8ef2b18be144612014.(DOI:10.6084/M9.FIGSHARE.1008029.V1).
Get Citation
Copy Citation Text
XING Yanchao, NIU Zhenhua. Infrared and Visible Image Fusion Based on Global Energy Features and Improved PCNN[J]. Infrared Technology, 2024, 46(8): 902