Infrared and Visible Image Fusion Method Based on Rolling Guidance Filter and Convolution Sparse Representation

Peipei Pei; Yanchun Yang; Jianwu Dang; Yangping Wang

doi:10.3788/LOP202259.1210001

[1] Du J, Li W S, Lu K et al. An overview of multi-modal medical image fusion[J]. Neurocomputing, 215, 3-20(2016).

[2] Ma J Y, Ma Y, Li C. Infrared and visible image fusion methods and applications: a survey[J]. Information Fusion, 45, 153-178(2019).

[3] Torabi A, Massé G, Bilodeau G A. An iterative integrated framework for thermal-visible image registration, sensor fusion, and people tracking for video surveillance applications[J]. Computer Vision and Image Understanding, 116, 210-221(2012).

[4] Xiao F Y. Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy[J]. Information Fusion, 46, 23-32(2019).

[5] Li S, Kang X, Hu J. Image fusion with guided filtering[J]. IEEE Transactions on Image Processing, 22, 2864-2875(2013).

[6] Ma J Y, Chen C, Li C et al. Infrared and visible image fusion via gradient transfer and total variation minimization[J]. Information Fusion, 31, 100-109(2016).

[7] Bavirisetti D P, Dhuli R. Two-scale image fusion of visible and infrared images using saliency detection[J]. Infrared Physics & Technology, 76, 52-64(2016).

[8] 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).

[9] Jiang Z T, Wu H, Zhou X L. Infrared and visible image fusion algorithm based on improved guided filtering and dual-channel spiking cortical model[J]. Acta Optica Sinica, 38, 0210002(2018).

[10] Chen J, Wu K L, Cheng Z et al. A saliency-based multiscale approach for infrared and visible image fusion[J]. Signal Processing, 182, 107936(2021).

[11] Zhang Q, Shen X, Xu L et al. Rolling guidance filter[M]. Fleet D, Pajdla T, Schiele B, et al. Computer vision-ECCV 2014, 8691, 815-830(2014).

[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] Wohlberg B. Efficient algorithms for convolutional sparse representations[J]. IEEE Transactions on Image Processing, 25, 301-315(2016).

[14] Yang Y C, Wang Y, Dang J W et al. Infrared and visible image fusion based on RGF and improved adaptive Unit-Linking PCNN[J]. Journal of Optoelectronics·Laser, 31, 401-410(2020).

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

[16] Liu X H, Chen Z B. Fusion of infrared and visible images based on multi-scale directional guided filter and convolutional sparse representation[J]. Acta Optica Sinica, 37, 1110004(2017).

[17] Dong A Y, Du Q Z, Long H et al. Multi-focus image fusion based on convolution sparse representation and neighborhood features[J]. Journal of Optoelectronics·Laser, 30, 442-450(2019).

[18] Zhang Y, Zhang L J, Bai X Z et al. Infrared and visual image fusion through infrared feature extraction and visual information preservation[J]. Infrared Physics & Technology, 83, 227-237(2017).

[19] Fu Z Z, Zhao Y F, Xu Y W et al. Gradient structural similarity based gradient filtering for multi-modal image fusion[J]. Information Fusion, 53, 251-268(2020).

[20] Zhang Y, Liu Y, Sun P et al. IFCNN: a general image fusion framework based on convolutional neural network[J]. Information Fusion, 54, 99-118(2020).

[21] Ma J Y, Zhou Y. Infrared and visible image fusion via gradientlet filter[J]. Computer Vision and Image Understanding, 197, 103016(2020).

[22] Shen Y, Wu Z D, Wang X P et al. Tetrolet transform image fusion algorithm based on fuzzy operator[J]. Journal of Frontiers of Computer Science and Technology, 9, 1132-1138(2015).

[23] Wang Z, Bovik A C. A universal image quality index[J]. IEEE Signal Processing Letters, 9, 81-84(2002).