XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/6: REMOTE SENSING DATA FUSION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES Huanfeng Shen

Document type:: Multivolume work

Structure type:: Chapter

= à RMSE, = x= I” (21) NaN. Oz, x Et b*b CC, m ET 5 (22) Xp Xp O x, x, 1x, ly VO = = ER A. Q3) ei, ox, mg, * my) ERGAS -100-Z- (24) 1 N UN SA z ————— Ny M Nx Gs Here, €, and x, represent the bth bands of the fused image and original image, Oi x is the covariance between X, and x,, mz and, their means, and c, and c, their standard deviations. The ideal values of the RMSE, CC, UIQI, ERGAS and SA are, respectively, 0, 1, 1, 0 and 0. The evaluation results are shown in Table 1. It is seen that the integrated fusion method obtains the best evaluation values in terms of all the indices. This verifies the proposed method has the performance to integrate the complementary temporal-spatial-spectral images. information in multiple Table 1. Evaluation of the fusion results International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia MT fusion MS/HS PAN/HS Integrated fusion fusion fusion RMSE 20.040 20.460 16.012 8.818 CC 0.952 0.945 0.969 0.990 UIQI 0.950 0.943 0.967 0.990 ERGAS 6.365 6.570 4.916 2.662 SA 5.659 8.749 8.230 5.509 5. CONCLUSIONS This paper presents a fusion method for multiple temporal- spatial-spectral images based on the maximum a posteriori framework. Simulated experiments validated that the proposed method has good performance in terms of both visual inspection and quantitative evaluation. Future works would be carried out to test the proposed method using real remote sensing images. ACKNOWLEDGEMENTS This work was supported by the Major State Basic Research Development Program (973 Program) under Grant 2011CB707103, the National Natural Science Foundation under Grant 40971220, 41071269, the Hubei Natural Science Foundation under Grant 201 1CDA096, and the Foundation of State Key Laboratory of Remote Sensing Science under Grant OFSLRSS201114 REFERENCES Boggione, G.A., Pires, E.G., Santos, P.A. and Fonseca, L.M.G., 2003. Simulation of a panchromatic band by spectral combination of multispectral ETM+ bands. In: International | Symposium on Remote Sensing of Environmental (ISRSE), Hawai. Eismann, M. and Hardie, R., 2005. Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions. /EEE Transactions on Geoscience and Remote Sensing, 43(3): 455-465. Joshi, 1. and Jalobeanu, A., 2010. MAP Estimation for Multiresolution Fusion in Remotely Sensed Images Using an IGMRF Prior Mode. /EEE Transactions on Geoscience and Remote Sensing, 48(3): 1245 -1255. Li, Z. and Leung, H., 2009. Fusion of Multispectral and Panchromatic Images Using a Restoration-Based Method. IEEE Transactions on Geoscience and Remote Sensing, 47: 1482-1491. Luo, R.C., Chih-Chen, Y. and Kuo Lan, S., 2002. Multisensor fusion and integration: approaches, applications, and future research directions. /EEE Sensors Journal , 2(2): 107-119. Pohl, C. and van Genderen, J.L., 1998. Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19(5): 823-854. Schultz, R.R. and Stevenson, R.L., 1996. Extraction of high- resolution frames from video sequences. IEEE Transactions on Image Processing, 5(6): 996-1011. Shen, H., Ng, M.K., Li, P. and Zhang, L., 2009. Super Resolution Reconstruction Algorithm to MODIS Remote Sensing Images. 7he Computer Journal, 52(1): 90-100. Shen, H. and Zhang, L., 2009. A MAP-Based Algorithm for Destriping and Inpainting of Remotely Sensed Images. IEEE Transactions on Geoscience and Remote Sensing, 47 (5): 1492-1502. Shen, H.F., Liu, Y.L., Ai, T.H., Wang, Y. and Wu, B., 2010. Universal reconstruction method for radiometric quality improvement of remote sensing images. /nternational Journal of Applied Earth Observation and Geoinformation, 12(4): 278-286. Vega, M., Mateos, J., Molina, R. and Katsaggelos, A.K., 2009. Super-Resolution of Multispectral Images. The Computer Journal, 52(1): 153.

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