| Citation: | QU Jiahui, LI Yunsong, DONG Wenqian, et al. Remote sensing image fusion based on edge-preserving filtering and structure tensor[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(12): 2479-2488. doi: 10.13700/j.bh.1001-5965.2018.0345(in Chinese) |
The hyperspectral (HS) remote sensing image which contains abundant spectral information generally has low spatial resolution. While the panchromatic (PAN) remote sensing image has high spatial resolution. In order to fuse the HS and PAN remote sensing images, a new fusion algorithm based on edge-preserving filtering and structure tensor is proposed. First, to avoid low-frequency aliasing, an edge-preserving filter is introduced to extract the spatial information of the HS image. In order to sharpen the spatial information of the PAN image, an image enhancement approach is applied to the PAN image. Then, an adaptive weighting strategy which is based on the structure tensor is proposed to obtain the total spatial information. The presented adaptive weighting strategy which is different from the traditional fusion method reduces the spectral distortion and provides adequate spatial information. The injection matrix is finally constructed to reduce spectral and spatial distortion, and the fused image is generated by injecting the complete spatial information. Experimental results demonstrate that the proposed method provides more spatial information and preserves more spectral information compared with the state-of-art fusion methods.
| [1] |
LI Y S, HU J, ZHAO X, et al. Hyperspectral image super-resolution using deep convolutional neural network[J]. Neurocomputing, 2017, 266:29-41. doi: 10.1016/j.neucom.2017.05.024
|
| [2] |
MOOKAMBIGA A, GOMATHI V. Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery[J].Multidimensional Systems and Signal Processing, 2016, 27(4):863-889. doi: 10.1007/s11045-016-0415-2
|
| [3] |
TU T M, SU S C, SHYU H C, et al. A new look at IHS-like image fusion methods[J].Information Fusion, 2001, 2(3):177-186. doi: 10.1016/S1566-2535(01)00036-7
|
| [4] |
CHAVEZ P S, KWARTENG A Y.Extracting spectral contrast in Landsat thematic mapper image data using selective principal component analysis[J].Photogrammetric Engineering and Remote Sensing, 1989, 55(3):339-348.
|
| [5] |
LABEN C, BROWER B.Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening: United States Patent 6011875[P].2000-01-04.
|
| [6] |
QU J H, LI Y S, DONG W Q.Hyperspectral pansharpening with guided filter[J].IEEE Geoscience and Remote Sensing Letters, 2017, 14(11):2152-2156. doi: 10.1109/LGRS.2017.2755679
|
| [7] |
MALLAT S.A theory for multiresolution signal decomposition:The wavelet representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7):674-693. doi: 10.1109/34.192463
|
| [8] |
VIVONE G, RESTAINO R, MAURO D M, et al.Contrast and error-based fusion schemes for multispectral image pansharpening[J].IEEE Geoscience and Remote Sensing Letters, 2014, 11(5):930-934. doi: 10.1109/LGRS.2013.2281996
|
| [9] |
LIU J G.Smoothing filter based intensity modulation:A spectral preserve image fusion technique for improving spatial details[J].International Journal of Remote Sensing, 2000, 21(18):3461-3472. doi: 10.1080/014311600750037499
|
| [10] |
YOKOYA N, YAIRI T, IWASAKI A.Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion[J].IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(2):528-537. doi: 10.1109/TGRS.2011.2161320
|
| [11] |
SIMOES M, DIAS J B, ALMEIDA L B, et al.A convex formulation for hyperspectral image superresolution via subspace-based regularization[J].IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(6):3373-3388. doi: 10.1109/TGRS.2014.2375320
|
| [12] |
WEI Q, DIAS J M, DOBIGEON N, et al.Hyperspectral and multispectral image fusion based on a sparse representation[J].IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(7):3658-3668. doi: 10.1109/TGRS.2014.2381272
|
| [13] |
HE K, SUN J, TANG X.Guided image filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6):1397-1409. doi: 10.1109/TPAMI.2012.213
|
| [14] |
HARRIS C.A combined corner and edge detector[C]//Proceedings of the Alvey Vision Conference, 1988: 147-151.
|
| [15] |
WALD L, RANCHIN T, MANGOLINI M.Fusion of satellite images of different spatial resolutions:Assessing the quality of resulting images[J].Photogrammetric Engineering and Remote Sensing, 1997, 63(6):691-699.
|
| [16] |
LONCAN L, ALMEIDA L B, DIAS J M, et al.Hyperspectral pansharpening:A review[J].IEEE Geoscience Remote Sensing Magazine, 2015, 3(3):27-46. doi: 10.1109/MGRS.2015.2440094
|
| [17] |
ZHANG L, ZHANG L, TAO D, et al.On combining multiple features for hyperspectral remote sensing image classification[J].IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(3):879-893. doi: 10.1109/TGRS.2011.2162339
|
| [18] |
AIAZZI B, BARONTI S, SELVA M.Improving component substitution pansharpening through multivariate regression of MS+pan data[J].IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(10):3230-3239. doi: 10.1109/TGRS.2007.901007
|
| [19] |
LIAO W, HUANG X, COILLIE F, et al.Processing of multiresolution thermal hyperspectral and digital color data:Outcome of the 2014 IEEE GRSS data fusion contest[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(6):2984-2996. doi: 10.1109/JSTARS.2015.2420582
|