The PAN and MS image fusion algorithm based on adaptive guided filtering and gradient information regulation
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[1] Rick S. Blum,et al. Fusing synergistic information from multi-sensor images: An overview from implementation to performance assessment , 2018, Inf. Fusion.
[2] Yu Liu,et al. Simultaneous image fusion and denoising with adaptive sparse representation , 2015, IET Image Process..
[3] Xiaojun Wu,et al. Image Fusion With Contextual Statistical Similarity and Nonsubsampled Shearlet Transform , 2017, IEEE Sensors Journal.
[4] Shiqian Wu,et al. Weighted Guided Image Filtering , 2016, IEEE Transactions on Image Processing.
[5] Liangpei Zhang,et al. A Remote Sensing Image Fusion Method Based on the Analysis Sparse Model , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[6] Josef Kittler,et al. Infrared and Visible Image Fusion using a Deep Learning Framework , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).
[7] David A. Clausi,et al. Comparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[8] Yalou Huang,et al. Multisensor Information Fusion for People Tracking With a Mobile Robot: A Particle Filtering Approach , 2015, IEEE Transactions on Instrumentation and Measurement.
[9] Gabriele Moser,et al. Decision Fusion With Multiple Spatial Supports by Conditional Random Fields , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[10] Mingjing Li,et al. Review of image fusion algorithm based on multiscale decomposition , 2013, Proceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC).
[11] C. V. Jiji,et al. A novel remote sensing image fusion algorithm using ICA bases , 2015, 2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR).
[12] Michael Meinild Nielsen,et al. Remote sensing for urban planning and management: The use of window-independent context segmentation to extract urban features in Stockholm , 2015, Comput. Environ. Urban Syst..
[13] Bin Luo,et al. Decision-Based Fusion for Pansharpening of Remote Sensing Images , 2013, IEEE Geoscience and Remote Sensing Letters.
[14] Hassan Ghassemian,et al. A review of remote sensing image fusion methods , 2016, Inf. Fusion.
[15] Xiao Xiang Zhu,et al. Data Fusion and Remote Sensing: An ever-growing relationship , 2016, IEEE Geoscience and Remote Sensing Magazine.
[16] Johannes R. Sveinsson,et al. Quantitative Quality Evaluation of Pansharpened Imagery: Consistency Versus Synthesis , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[17] Xavier Otazu,et al. Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[18] Qingshan Liu,et al. Improving the Spatial Resolution of Landsat TM/ETM+ Through Fusion With SPOT5 Images via Learning-Based Super-Resolution , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[19] P. Milanfar,et al. Multiscale principal components analysis for image local orientation estimation , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..
[20] Vijay Solanky,et al. Pixel-level image fusion techniques in remote sensing: a review , 2016, Spatial Information Research.
[21] Zhengguo Li,et al. Gradient Domain Guided Image Filtering , 2015, IEEE Transactions on Image Processing.
[22] Xiangyu Liu,et al. Remote Sensing Image Fusion Based on Two-Stream Fusion Network , 2017, MMM.
[23] Farhad Samadzadegan,et al. Object Recognition Based on the Context Aware Decision-Level Fusion in Multiviews Imagery , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[24] James M. Conrad,et al. A survey of multisensor fusion techniques, architectures and methodologies , 2017, SoutheastCon 2017.
[25] Roberto Manduchi,et al. Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).
[26] H. Ghassemian,et al. Improving hyperspectral image classification by combining spectral, texture, and shape features , 2015 .
[27] Abhishek Dey,et al. Remote sensing image fusion using Statistical Univariate Finite Mixture Model in Shearlet Domain , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
[28] Jun Zhou,et al. Object Classification via Feature Fusion Based Marginalized Kernels , 2015, IEEE Geoscience and Remote Sensing Letters.
[29] Wenda Zhao,et al. Gradient entropy metric and p-Laplace diffusion constraint-based algorithm for noisy multispectral image fusion , 2016, Inf. Fusion.
[30] Jian Sun,et al. Guided Image Filtering , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Andrea Garzelli,et al. Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis , 2002, IEEE Trans. Geosci. Remote. Sens..
[32] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[33] Xiaosong Li,et al. Multifocus image fusion by combining with mixed-order structure tensors and multiscale neighborhood , 2016, Inf. Sci..
[34] P. Maillard,et al. SPECTRAL-TEXTURAL IMAGE CLASSIFICATION IN A SEMIARID ENVIRONMENT , 2006 .
[35] Leen-Kiat Soh,et al. Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices , 1999, IEEE Trans. Geosci. Remote. Sens..