12.1.4.9 Image and Sensor Fusion for Cartography and Aerial Images, Satellite Images, Remote Sensing

Chapter Contents (Back)
Fusion. Sensor Fusion. Cartography. Remote Sensing.
See also Fusion of LANDSAT or Sentinel Images.
See also Fusion of Hyperspectral Images.
See also Pansharpening, Fusion of Aerial Images.
See also Super Resolution for Remote Sensing Applications.

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Clement, V., Giraudon, G., Houzelle, S., Sandakly, F.,
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IEEE Top Reference. BibRef 9307
Earlier:
Interpretation of Remotely Sensed Images in a Context of Multisensor Fusion,
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Clement, V., Giraudon, G., Houzelle, S.,
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Mascarenhas, N.D.A., Banon, G.J.F., Candeias, A.L.B.,
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Multispectral image data fusion using POCS and super-resolution,
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Elsevier DOI Remote sensing; Image interpolation; POCS: Projections onto convex sets. 0605
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Wald, L., Ranchin, T., Mangolini, M.,
Fusion of Satellite Images of Different Spatial Resolutions: Assessing the Quality of Resulting Images,
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Wald, L.,
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GeoRS(37), No. 3, May 1999, pp. 1190.
IEEE Top Reference. BibRef 9905

Boo, K.J., Bose, N.K.,
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IEEE Top Reference. 9710
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Ng, M.K.[Michael K.], Koo, J.[Jaehoon], Bose, N.K.,
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IJIST(12), No. 1, 2002, pp. 35-42.
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Wen, Y.W.[You-Wei], Ng, M.K.[Michael K.], Ching, W.K.[Wai-Ki],
High-resolution image reconstruction from rotated and translated low-resolution images with multisensors,
IJIST(14), No. 2, 2004, pp. 75-83.
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Ng, M.K.[Michael K.], Bose, N.K.,
Fast color image restoration with multisensors,
IJIST(12), No. 5, 2002, pp. 189-197.
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Ng, M.K.[Michael K.], Kwan, W.C.,
MAP regularized image reconstruction with multisensors,
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Jin, Z.M.[Zheng-Meng], Zhang, J.K.[Jun-Kang], Min, L.H.[Li-Hua], Ng, M.K.[Michael K.],
A Variational Model for Spatially Weighting in Image Fusion,
SIIMS(14), No. 2, 2021, pp. 441-469.
DOI Link 2107
BibRef

Ge, H.M.[Huan-Min], Chen, W.[Wengu], Ng, M.K.[Michael K.],
New Restricted Isometry Property Analysis for L_1-L_2 Minimization Methods,
SIIMS(14), No. 2, 2021, pp. 530-557.
DOI Link 2107
BibRef

Huet, F.[Florence], Philipp-Foliguet, S.[Sylvie],
Fusion of Images Interpreted by a New Fuzzy Classifier,
PAA(1), No. 4, 1998, pp. 231-247. BibRef 9800
Earlier:
Fusion of Images after Segmentation by Various Operators and Interpretation by a Multi-Scale Fuzzy Classification,
ICPR98(Vol II: 1843-1845).
IEEE DOI 9808
BibRef
And:
A Multi-Scale Fuzzy Classification by KNN: Application to the Interpretation of Aerial Images,
ICPR98(Vol I: 96-98).
IEEE DOI 9808
BibRef

Zhukov, B.S., Oertel, D.A.,
Modeling of the Fusion of Imaging Spectrometer and Multispectral Scanner Data with a Different Spatial-Resolution,
EORS(14), No. 5, 1997, pp. 723-739. 9804
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Solberg, A.H.S.[Anne H. Schistad],
Contextual Data Fusion Applied to Forest Map Revision,
GeoRS(37), No. 3, May 1999, pp. 1234.
IEEE Top Reference. BibRef 9905
Earlier:
Texture Fusion and Classification Based on Flexible Discriminant Analysis,
ICPR96(II: 596-600).
IEEE DOI 9608
(Norwegian Computing Center, N) BibRef

Price, J.C.,
Combining Multispectral Data of Differing Spatial Resolution,
GeoRS(37), No. 3, May 1999, pp. 1199.
IEEE Top Reference. BibRef 9905

Melgani, F.[Farid], Serpico, S.B.[Sebastiano B.],
A statistical approach to the fusion of spectral and spatio-temporal contextual information for the classification of remote-sensing images,
PRL(23), No. 9, July 2002, pp. 1053-1061.
Elsevier DOI 0205
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Moser, G., Serpico, S.B.,
Combining Support Vector Machines and Markov Random Fields in an Integrated Framework for Contextual Image Classification,
GeoRS(51), No. 5, May 2013, pp. 2734-2752.
IEEE DOI 1305
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Melgani, F.[Farid], Serpico, S.B.[Sebastiano B.],
A markov random field approach to spatio-temporal contextual image classification,
GeoRS(41), No. 11, November 2003, pp. 2478-2487.
IEEE Abstract. 0311
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Datcu, M., Melgani, F., Piardi, A., Serpico, S.B.,
Multisource data classification with dependence trees,
GeoRS(40), No. 3, March 2002, pp. 609-617.
IEEE Top Reference. 0206
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Ranchin, T.[Thierry], Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano], Wald, L.[Lucien],
Image fusion: The ARSIS concept and some successful implementation schemes,
PandRS(58), No. 1, June 2003, pp. 4-18.
Elsevier DOI 0307
BibRef

Aiazzi, B., Alparone, L., Baronti, S., Cappellini, V., Carlà, R., Mortelli, L.,
Pyramid-based multi-sensor image data fusion with enhancement of textural features,
CIAP97(I: 87-94).
Springer DOI 9709
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Guidi, G., Beraldin, J.A., Ciofi, S., Atzeni, C.,
Fusion of range camera and photogrammetry: A systematic procedure for improving 3-D models metric accuracy,
SMC-B(33), No. 4, August 2003, pp. 667-676.
IEEE Abstract. 0308
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Schiewe, J.[Jochen],
Integration of multi-sensor data for landscape modeling using a region-based approach,
PandRS(57), No. 5-6, April 2003, pp. 371-379.
Elsevier DOI 0307
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Chen, D.M.[Dong-Mei], Stow, D.[Douglas],
Strategies for Integrating Information from Multiple Spatial Resolutions into Land-Use/ Land-Cover Classification Routines,
PhEngRS(69), No. 11, November 2003, pp. 1279-1288.
WWW Link. 0401
Three strategies for integrating image information from different spatial resolutions into classification routines are developed and tested. BibRef

Pinzon, J.E., Pierce, J.F., Tucker, C.J., Brown, M.E.,
Evaluating coherence of natural images by smoothness membership in Besov spaces,
GeoRS(39), No. 9, September 2001, pp. 1879-1889.
IEEE Top Reference. 0111
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Morisette, J.T.[Jeffrey T.], Nickeson, J.E.[Jaime E.], Davis, P.[Paul], Wang, Y.J.[Yu-Jie], Tian, Y.H.[Yu-Hong], Woodcock, C.E.[Curtis E.], Shabanov, N.[Nikolay], Hansen, M.[Matthew], Cohen, W.B.[Warren B.], Oetter, D.R.[Doug R.], Kennedy, R.E.[Robert E.],
High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA Scientific Data Purchase,
RSE(88), No. 1-2, November 2003, pp. 100-110.
Elsevier DOI 0401
BibRef

Shi, W.Z.[Wen-Zhong], Zhu, C.Q.[Chang-Qing], Zhu, C.Y.[Cai-Ying], Yang, X.M.[Xiao-Mei],
Multi-Band Wavelet for Fusing SPOT Panchromatic and Multispectral Images,
PhEngRS(69), No. 5, May 2003, pp. 513-520.
WWW Link. 0307
A three-band wavelet is implemented to fuse 10-m SPOT panchromatic and 30-m multispectral TM images, method is compared with previous methods such as the two-band wavelet and IHS methods for image fusion. BibRef

Shi, W.Z.[Wen-Zhong], Zhu, C.Q.[Chang-Qing], Zhu, S.L.[Shu-Long],
Fusing Ikonos Images by a Four-band Wavelet Transformation Method,
PhEngRS(73), No. 11, November 2007, pp. 1285-1292.
WWW Link. 0709
A fourband wavelet fusion method for fusing one-meter panchromatic and four-meter multispectral imagery. BibRef

Gonzalez-Audicana, M., Saleta, J.L., Catalan, R.G., Garcia, R.,
Fusion of Multispectral and Panchromatic Images Using Improved IHS and PCA Mergers Based on Wavelet Decomposition,
GeoRS(42), No. 6, June 2004, pp. 1291-1299.
IEEE Abstract. 0407
BibRef

Maselli, F., Chiesi, M.,
Integration of High- and Low-Resolution Satellite Data to Estimate Pine Forest Productivity in a Mediterranean Coastal Area,
GeoRS(43), No. 1, January 2005, pp. 135-143.
IEEE Abstract. 0501
BibRef

Habib, A.[Ayman], Al-Ruzouq, R.[Rami],
Semi-Automatic Registration of Multi-Source Satellite Imagery with Varying Geometric Resolutions,
PhEngRS(71), No. 3, March 2005, pp. 325-332. A semi-automatic image registration paradigm that can handle multi-source satellite imagery with varying geometric resolutions.
WWW Link. 0509
BibRef

Li, Z.H.[Zhen-Hua], Jing, Z.L.[Zhong-Liang], Yang, X.H.[Xu-Hong], Sun, S.Y.[Shao-Yuan],
Color transfer based remote sensing image fusion using non-separable wavelet frame transform,
PRL(26), No. 13, 1 October 2005, pp. 2006-2014.
Elsevier DOI 0509
BibRef

Tadesse, T.[Tsegaye], Brown, J.F.[Jesslyn F.], Hayes, M.J.[Michael J.],
A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains,
PandRS(59), No. 4, June 2005, pp. 244-253.
Elsevier DOI 0509
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Gonzalez-Audicana, M., Otazu, X., Fors, O., Alvarez-Mozos, J.,
A Low Computational-Cost Method to Fuse IKONOS Images Using the Spectral Response Function of Its Sensors,
GeoRS(44), No. 6, June 2006, pp. 1683-1691.
IEEE DOI 0606
BibRef

Joshi, M.V., Bruzzone, L., Chaudhuri, S.,
A Model-Based Approach to Multiresolution Fusion in Remotely Sensed Images,
GeoRS(44), No. 9, September 2006, pp. 2549-2562.
IEEE DOI 0609
BibRef

Garcia-Haro, F.J., Camacho-de Coca, F., Melia, J.,
A Directional Spectral Mixture Analysis Method: Application to Multiangular Airborne Measurements,
GeoRS(44), No. 2, February 2006, pp. 365-377.
IEEE DOI 0602
Combine multiple signatures. BibRef

Koch, A.[Andreas], Heipke, C.[Christian],
Semantically correct 2.5D GIS data -- The integration of a DTM and topographic vector data,
PandRS(61), No. 1, October 2006, pp. 23-32.
Elsevier DOI 0610
DTM; Integration; Adjustment; Modelling BibRef

Ferguson, R.L.[Randolph L.], Krouse, C.[Charles], Patterson, M.[Marlene], Hare, J.A.[Jonathan A.],
Automated Thematic Registration of NOAA, CoastWatch, and AVHRR Images,
PhEngRS(72), No. 6, June 2006, pp. 677-686.
WWW Link. 0610
Mean radial error less than one pixel was robust to cloud cover. BibRef

Inglada, J., Muron, V., Pichard, D., Feuvrier, T.,
Analysis of Artifacts in Subpixel Remote Sensing Image Registration,
GeoRS(45), No. 1, January 2007, pp. 254-264.
IEEE DOI 0701
BibRef

Pradhan, P.S., King, R.L., Younan, N.H., Holcomb, D.W.,
Estimation of the Number of Decomposition Levels for a Wavelet-Based Multiresolution Multisensor Image Fusion,
GeoRS(44), No. 12, December 2006, pp. 3674-3686.
IEEE DOI 0701
BibRef

Gangkofner, U.G.[Ute G.], Pradhan, P.S.[Pushkar S.], Holcomb, D.W.[Derrold W.],
Optimizing the High-pass Filter Addition Technique for Image Fusion,
PhEngRS(74), No. 9, September 2008, pp. 1107-1118.
WWW Link. 0804
An upgraded methodology for High-Pass adding-based image fusion and comparison of results with wavelet-based image fusion results using spectral and spatial metrics. BibRef

Wong, A.[Alexander], Clausi, D.A.[David A.],
ARRSI: Automatic Registration of Remote-Sensing Images,
GeoRS(45), No. 5, May 2007, pp. 1483-1493.
IEEE DOI 0704
BibRef

Wong, A.[Alexander], Clausi, D.A.[David A.],
AISIR: Automated inter-sensor/inter-band satellite image registration using robust complex wavelet feature representations,
PRL(31), No. 10, 15 July 2010, pp. 1160-1167.
Elsevier DOI 1008
Image registration; Inter-sensor; Inter-band; Complex wavelet feature representations; Remote sensing BibRef

Wong, A.[Alexander],
Simultaneous multi-modal registration of multiple images based on multi-dimensional joint phase moment distributions,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kern, J.P.[Jeffrey P.], Pattichis, M.S.[Marios S.],
Robust Multispectral Image Registration Using Mutual-Information Models,
GeoRS(45), No. 5, May 2007, pp. 1494-1505.
IEEE DOI 0704
BibRef

Kalpoma, K.A., Kudoh, J.I.,
Image Fusion Processing for IKONOS 1-m Color Imagery,
GeoRS(45), No. 10, October 2007, pp. 3075-3086.
IEEE DOI 0711
BibRef

Buntilov, V., Bretschneider, T.R.,
A Content Separation Image Fusion Approach: Toward Conformity Between Spectral and Spatial Information,
GeoRS(45), No. 10, October 2007, pp. 3252-3263.
IEEE DOI 0711
BibRef

Li, R.X.[Rong-Xing], Zhou, F.[Feng], Niu, X.[Xutong], Di, K.C.[Kai-Chang],
Integration of Ikonos and QuickBird Imagery for Geopositioning Accuracy Analysis,
PhEngRS(73), No. 9, September 2007, pp. 1067-1075.
WWW Link. 0709
The integration of Ikonos and QuickBird imagery is feasible and can improve 3D geopositioning accuracy using proper combinations of images. BibRef

Chen, S.H.[Shao-Hui], Su, H.B.[Hong-Bo], Zhang, R.H.[Ren-Hua], Tian, J.[Jing],
Fusing remote sensing images using a trous wavelet transform and empirical mode decomposition,
PRL(29), No. 3, 1 February 2008, pp. 330-342.
Elsevier DOI 0801
Image fusion; A trous wavelet transform; Empirical mode decomposition; Dyadic wavelet transform
See also Depth image enlargement using an evolutionary approach. BibRef

Cakir, H.I.[Halil I.], Khorram, S.[Siamak],
Pixel Level Fusion of Panchromatic and Multispectral Images Based on Correspondence Analysis,
PhEngRS(74), No. 2, February 2008, pp. 183-192.
WWW Link. 0803
A pixel level data fusion approach based on correspondence analysis for high spatial and spectral resolution satellite data. BibRef

Hester, D.B.[David Barry], Cakir, H.I.[Halil I.], Nelson, S.A.C.[Stacy A.C.], Khorram, S.[Siamak],
Per-pixel Classification of High Spatial Resolution Satellite Imagery for Urban Land-cover Mapping,
PhEngRS(74), No. 4, April 2008, pp. 463-472.
WWW Link. 0804
Image fusion, spectral-based classifi cation, and GIS-based map refi nement methods used to derive an urban land-cover map from high spatial resolution satellite data. BibRef

Aanæs, H.[Henrik], Sveinsson, J.R.[Johannes R.], Nielsen, A.A.[Allan Aasbjerg], Bøvith, T.[Thomas], Benediktsson, J.A.[Jón Atli],
Model-Based Satellite Image Fusion,
GeoRS(46), No. 5, May 2008, pp. 1336-1346.
IEEE DOI 0804
BibRef

Gupta, P., Patadia, F., Christopher, S.A.,
Multisensor Data Product Fusion for Aerosol Research,
GeoRS(46), No. 5, May 2008, pp. 1407-1415.
IEEE DOI 0804
BibRef

Santos, C.[Carolina], Messina, J.P.[Joseph P.],
Multi-Sensor Data Fusion for Modeling African Palm in the Ecuadorian Amazon,
PhEngRS(74), No. 6, June 2008, pp. 711-724.
WWW Link. 0711
A significant improvement in the classification accuracy obtained through the fusion of optical and RADARSAT texture measures as compared to single sensor classifications. BibRef

Ancuti, C.[Cosmin], Haber, T.[Tom], Mertens, T.[Tom], Bekaert, P.[Philippe],
Video enhancement using reference photographs,
VC(24), No. 7-9, July 2008, pp. xx-yy.
Springer DOI 0804
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Zhao, Y.Q., Gong, P., Pan, Q.,
Object Detection by Spectropolarimeteric Imagery Fusion,
GeoRS(46), No. 10, October 2008, pp. 3337-3345.
IEEE DOI 0810
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Farah, I.R., Boulila, W., Ettabaa, K.S., Solaiman, B., Ahmed, M.B.,
Interpretation of Multisensor Remote Sensing Images: Multiapproach Fusion of Uncertain Information,
GeoRS(46), No. 12, December 2008, pp. 4142-4152.
IEEE DOI 0812
BibRef

Farah, I.R., Boulila, W., Ettabaa, K.S., Ahmed, M.B.,
Multiapproach System Based on Fusion of Multispectral Images for Land-Cover Classification,
GeoRS(46), No. 12, December 2008, pp. 4153-4161.
IEEE DOI 0812
BibRef

Ghazouani, F., Farah, I.R., Solaiman, B.,
A Multi-Level Semantic Scene Interpretation Strategy for Change Interpretation in Remote Sensing Imagery,
GeoRS(57), No. 11, November 2019, pp. 8775-8795.
IEEE DOI 1911
Semantics, Remote sensing, Visualization, Ontologies, Feature extraction, Data mining, Satellites, Change interpretation, temporal relations BibRef

Boulila, W.[Wadii], Farah, I.R.[Imed Riadh],
Multi-approach Satellite Images Fusion Based On Blind Sources Separation,
IJIG(11), No. 1, January 2011, pp. 117-136.
DOI Link 1103
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Radhadevi, P.V., Solanki, S.S., Jyothi, M.V., Nagasubramanian, V., Varadan, G.[Geeta],
Automated co-registration of images from multiple bands of Liss-4 camera,
PandRS(64), No. 1, January 2009, pp. 17-26.
Elsevier DOI 0804
Co-registration; In-flight calibration; Sensor model; Orbit-aligned; Geo-aligned BibRef

Aksoy, S.[Selim], Koperski, K.[Krzysztof], Tusk, C.[Carsten], Marchisio, G.[Giovanni],
Land Cover Classification with Multi-Sensor Fusion of Partly Missing Data,
PhEngRS(75), No. 5, May 2009, pp. 577-593.
WWW Link. 0904
Decision tree classifiers can be learned with alternative decision nodes for handling missing data in multi-source information fusion where one or more measurements do not exist for some locations. BibRef

Li, Z., Leung, H.,
Fusion of Multispectral and Panchromatic Images Using a Restoration-Based Method,
GeoRS(47), No. 5, May 2009, pp. 1482-1491.
IEEE DOI 0904
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Saadi, N.M., Aboud, E., Watanabe, K.,
Integration of DEM, ETM+, Geologic, and Magnetic Data for Geological Investigations in the Jifara Plain, Libya,
GeoRS(47), No. 10, October 2009, pp. 3389-3398.
IEEE DOI 0910
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Flitti, F.[Farid], Collet, C.[Christophe], Slezak, E.,
Image fusion based on pyramidal multiband multiresolution markovian analysis,
SIViP(3), No. 3, September 2009, pp. xx-yy.
Springer DOI 0910
BibRef

Flitti, F.[Farid], Bennamoun, M.[Mohammed], Huynh, D.[Du], Bermak, A.[Amine], Collet, C.[Christophe],
Probabilistic Satellite Image Fusion,
CAIP09(410-418).
Springer DOI 0909
BibRef

Eikvil, L.[Line], Holden, M.[Marit], Huseby, R.B.[Ragnar Bang],
Adaptive Registration of Remote Sensing Images using Supervised Learning,
PhEngRS(75), No. 11, November 2009, pp. 1297-1307.
WWW Link. 1001
A novel approach for registration of time series of remote sensing images, using supervised learning and a region based strategy to adapt the registration to image characteristics. BibRef

Joshi, M., Jalobeanu, A.,
MAP Estimation for Multiresolution Fusion in Remotely Sensed Images Using an IGMRF Prior Model,
GeoRS(48), No. 3, March 2010, pp. 1245-1255.
IEEE DOI 1003
BibRef

Yang, G., Pu, R., Huang, W., Wang, J., Zhao, C.,
A Novel Method to Estimate Subpixel Temperature by Fusing Solar-Reflective and Thermal-Infrared Remote-Sensing Data With an Artificial Neural Network,
GeoRS(48), No. 4, April 2010, pp. 2170-2178.
IEEE DOI 1003
BibRef

Metwalli, M.R.[Mohamed R.], Nasr, A.H.[Ayman H.], Allah, O.S.F.[Osama S. Farag], El-Rabaie, S., El-Samie, F.E.A.[Fathi E. Abd],
Satellite image fusion based on principal component analysis and high-pass filtering,
JOSA-A(27), No. 6, June 2010, pp. 1385-1394.
WWW Link. 1006
BibRef

Fan, X., Rhody, H., Saber, E.,
A Spatial-Feature-Enhanced MMI Algorithm for Multimodal Airborne Image Registration,
GeoRS(48), No. 6, June 2010, pp. 2580-2589.
IEEE DOI 1006
BibRef

Mahyari, A.G., Yazdi, M.,
Fusion of panchromatic and multispectral images using temporal fourier transform,
IET-IPR(4), No. 4, August 2010, pp. 255-260.
DOI Link 1008
BibRef

Ramakrishnan, N., Ertin, E., Moses, R.L.,
Enhancement of Coupled Multichannel Images Using Sparsity Constraints,
IP(19), No. 8, August 2010, pp. 2115-2126.
IEEE DOI 1008
BibRef

Wang, T.H., Fang, C.W., Sung, M.C., Lien, J.J.J.,
Photography Enhancement Based on the Fusion of Tone and Color Mappings in Adaptive Local Region,
IP(19), No. 12, December 2010, pp. 3089-3105.
IEEE DOI 1011
BibRef

Wang, T.H., Chiu, C.W., Wu, W.C., Wang, J.W., Lin, C.Y., Chiu, C.T., Liou, J.J.,
Pseudo-Multiple-Exposure-Based Tone Fusion With Local Region Adjustment,
MultMed(17), No. 4, April 2015, pp. 470-484.
IEEE DOI 1503
Brightness BibRef

Zubko, V., Leptoukh, G.G., Gopalan, A.,
Study of Data-Merging and Interpolation Methods for Use in an Interactive Online Analysis System: MODIS Terra and Aqua Daily Aerosol Case,
GeoRS(48), No. 12, December 2010, pp. 4219-4235.
IEEE DOI 1011

See also Principal Component Analysis of Remote Sensing of Aerosols Over Oceans. BibRef

Saulquin, B., Gohin, F., Garrello, R.,
Regional Objective Analysis for Merging High-Resolution MERIS, MODIS/Aqua, and SeaWiFS Chlorophyll-a Data From 1998 to 2008 on the European Atlantic Shelf,
GeoRS(49), No. 1, January 2011, pp. 143-154.
IEEE DOI 1101
BibRef

Choi, J., Yu, K., Kim, Y.,
A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement,
GeoRS(49), No. 1, January 2011, pp. 295-309.
IEEE DOI 1101
BibRef

Sadhasivam, S.K.[Senthil Kumar], Keerthivasan, M.B.[Mahesh Bharath], Muttan, S.,
Implementation of Max Principle with PCA in image fusion for Surveillance and Navigation Application,
ELCVIA(10), No. 1, 2011, pp. xx-yy.
DOI Link 1112
BibRef

Xu, M.[Min], Chen, H.[Hao], Varshney, P.K.,
An Image Fusion Approach Based on Markov Random Fields,
GeoRS(49), No. 12, December 2011, pp. 5116-5127.
IEEE DOI 1201
BibRef

Brook, A., Ben-Dor, E.,
Automatic Registration of Airborne and Spaceborne Images by Topology Map Matching with SURF Processor Algorithm,
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DOI Link 1203
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Guthier, B.[Benjamin], Kopf, S.[Stephan], Effelsberg, W.[Wolfgang],
Algorithms for a real-time HDR video system,
PRL(34), No. 1, 1 January 2013, pp. 25-33.
Elsevier DOI 1211
BibRef
Earlier:
Histogram-based image registration for real-time high dynamic range videos,
ICIP10(145-148).
IEEE DOI 1009
HDR video; Multi-spectrum video acquisition; Image registration; Video
See also Robust tracking for interactive social video. BibRef

Li, S., Yin, H., Fang, L.,
Remote Sensing Image Fusion via Sparse Representations Over Learned Dictionaries,
GeoRS(51), No. 9, 2013, pp. 4779-4789.
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IEEE DOI 1402
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Springer DOI 1511
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atmospheric optics, image registration, high resolution multitemporal images, homogeneous spectral properties, multiple displacement analysis, multitemporal VHR images,residual local misalignment, segmentation-based fine registration, standard registration, Correlation, Feature extraction, Geometry, Image color analysis, Image resolution, Image segmentation, object representative points, registration, remote sensing, urban areas BibRef

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Image segmentation, Semantics, Image analysis, Feature extraction, Machine learning, Data mining, Training, Deep learning, segmentation BibRef

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An Error-Bound-Regularized Sparse Coding for Spatiotemporal Reflectance Fusion,
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geophysical image processing BibRef

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Investigation of SMAP Fusion Algorithms With Airborne Active and Passive L-Band Microwave Remote Sensing,
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feature extraction, image matching, image registration, image segmentation, radar imaging, remote sensing, scale invariant feature transformation BibRef

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image matching, image registration, optical radar, remote sensing, synthetic aperture radar, LiDAR, SAR, automatic image registration, fast template matching scheme, feature descriptor, histogram of orientated phase congruency, light detection and ranging, map data, normalized correlation coefficient, optical radar, BibRef

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IEEE DOI 1708
Data integration, Monitoring, Remote sensing, Sensors, Spatial resolution, Spatiotemporal phenomena, Data fusion, nonlocal, reflectance prediction, similarity information, spatiotemporal BibRef

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IEEE DOI 1801
Cameras, Estimation, Image matching, Image resolution, Mars, Remote sensing, Systematics, High-resolution imaging, remote sensing BibRef

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Elsevier DOI 1905
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IEEE DOI 1907
Image coding, Spatial resolution, Sensors, Imaging, Image fusion, Fuses, Compressive sampling, data fusion, remote sensing, spectral imaging BibRef

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Feature extraction, Image coding, Apertures, Sensors, Optical imaging, Image resolution, spectral image classification BibRef

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Spatial resolution, Spatiotemporal phenomena, Remote sensing, Earth, Convolutional neural networks, Image fusion, temporal dependence (TD) BibRef

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ICIP18(1882-1886)
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Ye, X.H.[Xin-Hai], Xiong, F.C.[Feng-Chao], Lu, J.F.[Jian-Feng], Zhou, J.[Jun], Qian, Y.T.[Yun-Tao],
F3-Net: Feature Fusion and Filtration Network for Object Detection in Optical Remote Sensing Images,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zhang, Y.[Yi], Fu, L.[Lei], Li, Y.[Ying], Zhang, Y.N.[Yan-Ning],
HDFNet: Hierarchical Dynamic Fusion Network for Change Detection in Optical Aerial Images,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, Y.C.[Yan-Chao], Yang, W.[Wen], Sun, Y.[Ying], Chang, C.[Christine], Yu, J.[Jiya], Zhang, W.B.[Wen-Bo],
Fusion of Multispectral Aerial Imagery and Vegetation Indices for Machine Learning-Based Ground Classification,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
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Zhang, H.Y.[Hong-Yan], Song, Y.Y.[Yi-Yao], Han, C.[Chang], Zhang, L.P.[Liang-Pei],
Remote Sensing Image Spatiotemporal Fusion Using a Generative Adversarial Network,
GeoRS(59), No. 5, May 2021, pp. 4273-4286.
IEEE DOI 2104
Spatial resolution, Remote sensing, Earth, Spatiotemporal phenomena, Artificial satellites, Generators, spatiotemporal fusion BibRef

Iyer, G.[Geoffrey], Chanussot, J.[Jocelyn], Bertozzi, A.L.[Andrea L.],
A Graph-Based Approach for Data Fusion and Segmentation of Multimodal Images,
GeoRS(59), No. 5, May 2021, pp. 4419-4429.
IEEE DOI 2104
Image segmentation, Laser radar, Data integration, Laplace equations, Optical imaging, Optical sensors, Graphs, segmentation BibRef

Zheng, Z.G.[Zhong-Gang], Li, Q.M.[Qing-Mei], Fu, K.[Kun],
Evaluation Model of Remote Sensing Satellites Cooperative Observation Capability,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Shi, C.P.[Cui-Ping], Zhao, X.[Xin], Wang, L.G.[Li-Guo],
A Multi-Branch Feature Fusion Strategy Based on an Attention Mechanism for Remote Sensing Image Scene Classification,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
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Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
Remote Sensing Scene Image Classification Based on Dense Fusion of Multi-level Features,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Channel Multi-Group Fusion for Remote Sensing Scene Classification,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Wang, T.Y.[Tian-Yi], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Hierarchical-Wise Convolution Fusion for Remote-Sensing Scene Image Classification,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
Remote Sensing Scene Image Classification Based on Self-Compensating Convolution Neural Network,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Shi, C.P.[Cui-Ping], Ding, M.X.[Meng-Xiang], Wang, L.G.[Li-Guo], Pan, H.Z.[Hai-Zhu],
Learn by Yourself: A Feature-Augmented Self-Distillation Convolutional Neural Network for Remote Sensing Scene Image Classification,
RS(15), No. 23, 2023, pp. 5620.
DOI Link 2312
BibRef

Shi, C.P.[Cui-Ping], Zhang, X.L.[Xin-Lei], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
A Lightweight Convolutional Neural Network Based on Group-Wise Hybrid Attention for Remote Sensing Scene Classification,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Lin, J.Z.[Jian-Zhe], Yu, T.Z.[Tian-Ze], Mou, L.C.[Li-Chao], Zhu, X.X.[Xiao-Xiang], Ward, R.K.[Rabab Kreidieh], Wang, Z.J.[Z. Jane],
Unifying Top-Down Views by Task-Specific Domain Adaptation,
GeoRS(59), No. 6, June 2021, pp. 4689-4702.
IEEE DOI 2106
Task analysis, Generators, Data models, Correlation, Satellites, Semantics, Adaptation models, machine learning-predictive models BibRef

Lu, H.[Han], Qiao, D.Y.[Dan-Yu], Li, Y.X.[Yong-Xin], Wu, S.[Shuang], Deng, L.[Lei],
Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used?,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Koz, A.[Alper], Efe, U.[Ufuk],
Geometric- and Optimization-Based Registration Methods for Long-Wave Infrared Hyperspectral Images,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Luo, X.[Xin], Tong, X.H.[Xiao-Hua], Hu, Z.W.[Zhong-Wen],
Improving Satellite Image Fusion via Generative Adversarial Training,
GeoRS(59), No. 8, August 2021, pp. 6969-6982.
IEEE DOI 2108
Image fusion, Satellites, Training, Spatial resolution, Remote sensing, Deep learning, Sentinel-2 BibRef

Zhao, X.[Xin], Li, H.[Hui], Wang, P.[Ping], Jing, L.H.[Lin-Hai],
An Image Registration Method Using Deep Residual Network Features for Multisource High-Resolution Remote Sensing Images,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, S.Y.[Si-Yuan], Jiao, J.N.[Jian-Nan], Wang, C.[Chi],
Research on Polarized Multi-Spectral System and Fusion Algorithm for Remote Sensing of Vegetation Status at Night,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Nara, H.[Hideharu], Sawada, Y.[Yohei],
Global Change in Terrestrial Ecosystem Detected by Fusion of Microwave and Optical Satellite Observations,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Li, L.Z.[Liang-Zhi], Han, L.[Ling], Ding, M.T.[Ming-Tao], Cao, H.Y.[Hong-Ye], Hu, H.J.[Hui-Juan],
A deep learning semantic template matching framework for remote sensing image registration,
PandRS(181), 2021, pp. 205-217.
Elsevier DOI 2110
Registration, Deep learning, Semantic template, Semantic distribution probability, Remote sensing image, CNN BibRef

Stone, D.L.[David L.], Ravi, S.[Sumved], Benli, E.[Emrah], Motai, Y.I.[Yu-Ichi],
DeepFuseNet of Omnidirectional Far-Infrared and Visual Stream for Vegetation Detection,
GeoRS(59), No. 11, November 2021, pp. 9057-9070.
IEEE DOI 2111
Visualization, Feature extraction, Robots, Sensors, Vegetation mapping, Cameras, Sensor fusion, vegetation detection BibRef

Liu, Q.J.[Qing-Jie], Zhou, H.Y.[Huan-Yu], Xu, Q.Z.[Qi-Zhi], Liu, X.Y.[Xiang-Yu], Wang, Y.H.[Yun-Hong],
PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening,
GeoRS(59), No. 12, December 2021, pp. 10227-10242.
IEEE DOI 2112
BibRef
Earlier: A4, A5, A1, Only: ICIP18(873-877)
IEEE DOI 1809
BibRef
And: A4, A5, A1, Only:
Remote Sensing Image Fusion Based on Two-Stream Fusion Network,
MMMod18(I:428-439).
Springer DOI 1802
Generative adversarial networks, Generators, Neural networks, Training, Spatial resolution, Data models, residual learning. Remote sensing, Task analysis, Image fusion, pan-sharpening, GAN, remote sensing BibRef

Tan, Z.Y.[Zhen-Yu], Gao, M.L.[Mei-Ling], Li, X.H.[Xing-Hua], Jiang, L.C.[Liang-Cun],
A Flexible Reference-Insensitive Spatiotemporal Fusion Model for Remote Sensing Images Using Conditional Generative Adversarial Network,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Spatiotemporal phenomena, Data models, Remote sensing, Image resolution, Spatial resolution, spatiotemporal BibRef

Sun, W.W.[Wei-Wei], Ren, K.[Kai], Meng, X.C.[Xiang-Chao], Xiao, C.C.[Chen-Chao], Yang, G.[Gang], Peng, J.T.[Jiang-Tao],
A Band Divide-and-Conquer Multispectral and Hyperspectral Image Fusion Method,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Spatial resolution, Neural networks, Image fusion, Hyperspectral imaging, Bayes methods, Sun, Signal resolution, neural network framework BibRef

Fan, Z.L.[Zhong-Li], Liu, Y.X.[Yu-Xian], Liu, Y.X.[Yu-Xuan], Zhang, L.[Li], Zhang, J.J.[Jun-Jun], Sun, Y.S.[Yu-Shan], Ai, H.B.[Hai-Bin],
3MRS: An Effective Coarse-to-Fine Matching Method for Multimodal Remote Sensing Imagery,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Dhillon, M.S.[Maninder Singh], Dahms, T.[Thorsten], Kübert-Flock, C.[Carina], Steffan-Dewenter, I.[Ingolf], Zhang, J.[Jie], Ullmann, T.[Tobias],
Spatiotemporal Fusion Modelling Using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Xu, C.[Chuan], Liu, C.[Chang], Li, H.L.[Hong-Li], Ye, Z.W.[Zhi-Wei], Sui, H.G.[Hai-Gang], Yang, W.[Wei],
Multiview Image Matching of Optical Satellite and UAV Based on a Joint Description Neural Network,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Liu, X.Z.[Xiang-Zeng], Xue, J.P.[Jie-Peng], Xu, X.L.[Xue-Ling], Lu, Z.X.[Zi-Xiang], Liu, R.[Ruyi], Zhao, B.C.[Bo-Cheng], Li, Y.[Yunan], Miao, Q.G.[Qi-Guang],
Robust Multimodal Remote Sensing Image Registration Based on Local Statistical Frequency Information,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Khokhlova, M.[Margarita], Abadie, N.[Nathalie], Gouet-Brunet, V.[Valérie], Chen, L.M.[Li-Ming],
GisGCN: A Visual Graph-Based Framework to Match Geographical Areas through Time,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Yan, C.[Chuan], Fan, X.[Xiangsuo], Fan, J.L.[Jin-Long], Wang, N.[Nayi],
Improved U-Net Remote Sensing Classification Algorithm Based on Multi-Feature Fusion Perception,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Swinnen, E.[Else], Sterckx, S.[Sindy], Wirion, C.[Charlotte], Verbeiren, B.[Boud], Wens, D.[Dieter],
Harmonization of Multi-Mission High-Resolution Time Series: Application to BELAIR,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
To get cloud free analysis, data from multiple sensors. BibRef

Yao, Y.X.[Yong-Xiang], Zhang, Y.J.[Yong-Jun], Wan, Y.[Yi], Liu, X.[Xinyi], Yan, X.H.[Xiao-Hu], Li, J.Y.[Jia-Yuan],
Multi-Modal Remote Sensing Image Matching Considering Co-Occurrence Filter,
IP(31), 2022, pp. 2584-2597.
IEEE DOI 2204
Feature extraction, Image matching, Image edge detection, Remote sensing, Matched filters, Nonlinear distortion, log-polar descriptor BibRef

Zhang, Y.J.[Yong-Jun], Yao, Y.X.[Yong-Xiang], Wan, Y.[Yi], Liu, W.Y.[Wei-Yu], Yang, W.[Wupeng], Zheng, Z.[Zhi], Xiao, R.[Rang],
Histogram of the orientation of the weighted phase descriptor for multi-modal remote sensing image matching,
PandRS(196), 2023, pp. 1-15.
Elsevier DOI 2302
Multi-modal remote sensing image, Aggregation feature, Weighted phase orientation feature, Log-polar of regularized, Bidirectional matching BibRef

Ye, Y.X.[Yuan-Xin], Zhu, B.[Bai], Tang, T.F.[Teng-Feng], Yang, C.[Chao], Xu, Q.Z.[Qi-Zhi], Zhang, G.[Guo],
A robust multimodal remote sensing image registration method and system using steerable filters with first- and second-order gradients,
PandRS(188), 2022, pp. 331-350.
Elsevier DOI 2205
Multimodal images, SFOC, Fast-NCC, Integral feature images, Registration system BibRef

Rashwan, S.[Shaheera], Sheta, W.[Walaa],
A Metaheuristics Framework for Weighted Multi-band Image Fusion,
IJIG(22), No. 2, April 2022, pp. 2250016.
DOI Link 2205
BibRef

Fernandes, M.[Michael], Pletl, A.[Alexander], Thomas, N.[Nicolas], Rossi, A.P.[Angelo Pio], Elser, B.[Benedikt],
Generation and Optimization of Spectral Cluster Maps to Enable Data Fusion of CaSSIS and CRISM Datasets,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
Fusion of 2 Mars datasources. Color and Stereo Surface Imaging System. Compact Reconnaissance Imaging Spectrometer. BibRef

Gao, T.[Tong], Chen, H.[Hao], Lu, J.H.[Jun-Hong],
Coupled Heterogeneous Tucker Decomposition: A Feature Extraction Method for Multisource Fusion and Domain Adaptation Using Multisource Heterogeneous Remote Sensing Data,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Zhang, H.W.[Hong-Wei], Huang, F.[Fang], Hong, X.[Xiuchao], Wang, P.[Ping],
A Sensor Bias Correction Method for Reducing the Uncertainty in the Spatiotemporal Fusion of Remote Sensing Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Cheng, F.F.[Fei-Fei], Fu, Z.T.[Zhi-Tao], Tang, B.H.[Bo-Hui], Huang, L.[Liang], Huang, K.[Kun], Ji, X.R.[Xin-Ran],
STF-EGFA: A Remote Sensing Spatiotemporal Fusion Network with Edge-Guided Feature Attention,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
Edge features in fusion operation. BibRef

Li, L.Z.[Liang-Zhi], Han, L.[Ling], Ye, Y.X.[Yuan-Xin],
Self-Supervised Keypoint Detection and Cross-Fusion Matching Networks for Multimodal Remote Sensing Image Registration,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Ul Hoque, M.R.[Md Reshad], Wu, J.[Jian], Kwan, C.[Chiman], Koperski, K.[Krzysztof], Li, J.[Jiang],
ArithFusion: An Arithmetic Deep Model for Temporal Remote Sensing Image Fusion,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Yang, M.C.[Ming-Chuan], Xue, G.C.[Guan-Chang], Liu, B.T.[Bo-Tao], Yang, Y.[Yupu],
Dual Threshold Cooperative Sensing Based Dynamic Spectrum Sharing Algorithm for Integrated Satellite and Terrestrial System,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, L.H.[Long-Hao], Lan, C.Z.[Chao-Zhen], Wu, B.B.[Bei-Bei], Gao, T.[Tian], Wei, Z.J.[Zi-Jun], Yao, F.[Fushan],
A Method for Detecting Feature-Sparse Regions and Matching Enhancement,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Hou, H.[Huitai], Lan, C.Z.[Chao-Zhen], Xu, Q.[Qing], Lv, L.[Liang], Xiong, X.[Xin], Yao, F.[Fushan], Wang, L.H.[Long-Hao],
Attention-Based Matching Approach for Heterogeneous Remote Sensing Images,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Hou, Z.Y.[Zhao-Yang], Lv, K.[Kaiyun], Gong, X.Q.[Xun-Qiang], Wan, Y.T.[Yu-Ting],
A Remote Sensing Image Fusion Method Combining Low-Level Visual Features and Parameter-Adaptive Dual-Channel Pulse-Coupled Neural Network,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Li, H.Q.[Hao-Qing], Duvvuri, B.[Bhavya], Borsoi, R.[Ricardo], Imbiriba, T.[Tales], Beighley, E.[Edward], Erdogmus, D.[Deniz], Closas, P.[Pau],
Online fusion of multi-resolution multispectral images with weakly supervised temporal dynamics,
PandRS(196), 2023, pp. 471-489.
Elsevier DOI 2302
Multimodal image fusion, Online fusion, Bayesian filtering, Water mapping, Super-resolution BibRef

Jha, A.[Ankit], Bose, S.[Shirsha], Banerjee, B.[Biplab],
GAF-Net: Improving the Performance of Remote Sensing Image Fusion using Novel Global Self and Cross Attention Learning,
WACV23(6343-6352)
IEEE DOI 2302
Representation learning, Laser radar, Limiting, Benchmark testing, Feature extraction, Optical imaging, Optical sensors, visual reasoning BibRef

Misra, I.[Indranil], Rohil, M.K.[Mukesh Kumar], Moorthi, S.M.[S. Manthira], Dhar, D.[Debajyoti],
SPRINT: Spectra Preserving Radiance Image Fusion Technique using holistic deep edge spatial attention and Minnaert guided Bayesian probabilistic model,
SP:IC(113), 2023, pp. 116920.
Elsevier DOI 2303
Image fusion, Holistic Nested Edge Detection, Minnaert function, Digital elevation model, Remote sensing BibRef

Bai, S.[Shi], Zhao, J.[Jie],
A New Strategy to Fuse Remote Sensing Data and Geochemical Data with Different Machine Learning Methods,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Liu, H.[Hui], Yang, G.Q.[Guang-Qi], Deng, F.L.[Feng-Liang], Qian, Y.R.[Yu-Rong], Fan, Y.Y.[Ying-Ying],
MCBAM-GAN: The GAN Spatiotemporal Fusion Model Based on Multiscale and CBAM for Remote Sensing Images,
RS(15), No. 6, 2023, pp. 1583.
DOI Link 2304
BibRef

Liu, Z.Q.[Zhi-Qiang], Wang, Z.[Zhao], Zhao, Z.[Zhitao], Huo, L.[Lianzhi], Tang, P.[Ping], Zhang, Z.[Zheng],
Bandpass Alignment from Sentinel-2 to Gaofen-1 ARD Products with UNet-Induced Tile-Adaptive Lookup Tables,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Liang, C.B.[Chen-Bin], Dong, Y.Y.[Yun-Yun], Zhao, C.J.[Chang-Jun], Sun, Z.G.[Zeng-Guo],
A Coarse-to-Fine Feature Match Network Using Transformers for Remote Sensing Image Registration,
RS(15), No. 13, 2023, pp. 3243.
DOI Link 2307
BibRef

Liu, X.Z.[Xiang-Zeng], Xu, X.L.[Xue-Ling], Zhang, X.D.[Xiao-Dong], Miao, Q.G.[Qi-Guang], Wang, L.[Lei], Chang, L.[Liang], Liu, R.[Ruyi],
SRTPN: Scale and Rotation Transform Prediction Net for Multimodal Remote Sensing Image Registration,
RS(15), No. 14, 2023, pp. 3469.
DOI Link 2307
BibRef

Wang, Z.Y.[Zhi-Yuan], Fang, S.[Shuai], Zhang, J.[Jing],
Spatiotemporal Fusion Model of Remote Sensing Images Combining Single-Band and Multi-Band Prediction,
RS(15), No. 20, 2023, pp. 4936.
DOI Link 2310
BibRef

Yang, J.[Jian], Li, C.[Chen], Li, X.L.[Xue-Long],
AA-LMM: Robust Accuracy-Aware Linear Mixture Model for Remote Sensing Image Registration,
RS(15), No. 22, 2023, pp. 5314.
DOI Link 2311
BibRef

Pan, X.Y.[Xiao-Yu], Deng, M.[Muyuan], Ao, Z.[Zurui], Xin, Q.C.[Qin-Chuan],
An Adaptive Multiscale Generative Adversarial Network for the Spatiotemporal Fusion of Landsat and MODIS Data,
RS(15), No. 21, 2023, pp. 5128.
DOI Link 2311
BibRef

Ma, Y.Y.[Yu-Yang], Shen, Y.L.[Yong-Lin], Shen, G.[Guoling], Wang, J.[Jie], Xiao, W.[Wen], He, H.[Huiyang], Hu, C.L.[Chu-Li], Qin, K.[Kai],
STEPSBI: Quick spatiotemporal fusion with coarse- and fine-resolution scale transformation errors and pixel-based synthesis base image pair,
PandRS(206), 2023, pp. 1-15.
Elsevier DOI Code:
WWW Link. 2312
Scale transformation error, Pixel-based synthesized image, Land surface heterogeneity, Google Earth Engine, Spatiotemporal fusion BibRef

Youssef, M.[Mohamed], Bimber, O.[Oliver],
Fusion of Single and Integral Multispectral Aerial Images,
RS(16), No. 4, 2024, pp. 673.
DOI Link 2402
BibRef

Zhang, X.J.[Xing-Jian], Li, S.[Shuang], Tan, Z.Y.[Zhen-Yu], Li, X.H.[Xing-Hua],
Enhanced wavelet based spatiotemporal fusion networks using cross-paired remote sensing images,
PandRS(211), 2024, pp. 281-297.
Elsevier DOI Code:
WWW Link. 2405
Convolutional neural network, Remote sensing image, Spatiotemporal fusion, Wavelet transform BibRef

Geng, X.L.[Xue-Li], Jiao, L.C.[Li-Cheng], Li, L.L.[Ling-Ling], Liu, X.[Xu], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan],
Fast and Effective: Progressive Hierarchical Fusion Classification for Remote Sensing Images,
MultMed(26), 2024, pp. 9776-9789.
IEEE DOI 2410
Remote sensing, Feature extraction, Computer architecture, Semantics, Image classification, Decoding, progressive hierarchical fusion network (PHFNet) BibRef

Alparone, L.[Luciano], Arienzo, A.[Alberto], Garzelli, A.[Andrea],
Automatic Fine Co-Registration of Datasets from Extremely High Resolution Satellite Multispectral Scanners by Means of Injection of Residues of Multivariate Regression,
RS(16), No. 19, 2024, pp. 3576.
DOI Link 2410
BibRef

Wang, W.Q.[Wen-Qing], Jia, F.[Fei], Yang, Y.F.[Yi-Fei], Mu, K.[Kunpeng], Liu, H.[Han],
MDSCNN: Remote Sensing Image Spatial-Spectral Fusion Method via Multi-Scale Dual-Stream Convolutional Neural Network,
RS(16), No. 19, 2024, pp. 3583.
DOI Link 2410
BibRef

Li, Y.[Yang], Chen, F.[Feinan], Sui, T.[Tangyu], Ti, R.[Rufang], Cheng, W.H.[Wei-Hua], Hong, J.[Jin], Qiu, Z.W.[Zhen-Wei],
Interplay Between Atmospheric Correction and Fusion Techniques Enhances the Quality of Remote Sensing Image Fusion,
RS(16), No. 21, 2024, pp. 3916.
DOI Link 2411
BibRef

Li, Y.F.[Yun-Fei], Li, J.[Jun],
Investigating and Reducing the Impairment of Point Spread Effect for Spatiotemporal Fusion of Remote Sensing Imagery,
ICIP24(2676-2682)
IEEE DOI 2411
Earth, Artificial satellites, Accuracy, Distortion, Spatiotemporal phenomena, Satellite images, Spatial resolution, Point Spread Effect BibRef

Han, B.[Boran], Zhang, S.[Shuai], Shi, X.J.[Xing-Jian], Reichstein, M.[Markus],
Bridging Remote Sensors with Multisensor Geospatial Foundation Models,
CVPR24(27852-27862)
IEEE DOI Code:
WWW Link. 2410
Representation learning, Adaptation models, Scene classification, Predictive models, Optical imaging, Data models, Geospatial analysis BibRef