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Abstract: This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery, based on principal component analysis (PCA) and intensity-hue-saturation (IHS) transformations. The PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component, respectively. The enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation, and undertaking the inverse IHS transformation. The objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral image. On the basis of the visual and statistical analysis results of the experimental study, we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color distortion. It has potential advantages in image mapping optimization, object recognition, and weak information sharpening.

[1]Acerbi-Junior, F.W., Clevers, J.G.P.W., Schaepman, M.E., 2006. The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna. International Journal of Applied Earth Observation and Geoinformation, 8(4):278-288.

[2]Alparone, L., Baronti, S., Garzelli, A., Nencini, F., 2004. A global quality measurement of pan-sharpened multispectral imagery. IEEE Geoscience and Remote Sensing Letters, 1(4):313-317.

[3]Armenakis, C., Leduc, F., Cyr, I., Savopol, F., Cavayas, F., 2003. A comparative analysis of scanned maps and imagery for mapping applications. ISPRS Journal of Photogrammetry & Remote Sensing, 57(5-6):304-314.

[4]Bedini, E., 2010. Mineral mapping in the Kap Simpson complex, central East Greenland, using HyMap and ASTER remote sensing data. Advances in Space Research, 47(1):60-73.

[5]Canisius, F.X.J., Turral, H., 2003. Fusion Technique to Extract Detail Information from Moderate Resolution Data for Global Scale Image Map Production. Proceedings of the 30th International Symposium on Remote Sensing of Environment-Information for Risk Management and Sustainable Development, Honolulu, Hawaii, USA.

[6]Cengiz, O., Sener, E., Yagmurlu, F., 2005. A satellite image approach to the study of lineaments, circular structures and regional geology in the Golcuk Crater district and its environs (Isparta, SW Turkey). Journal of Asian Earth Sciences, 27(2):155-163.

[7]Chavez, P.S., Sides, S.C., Anderson, J.A., 1991. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic. Photogrammetric Engineering and Remote Sensing, 57(3):295-303.

[8]Chen, C.M., Hepner, G.F., Forster, R.R., 2003. Fusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features. ISPRS Journal of Photogrammetry & Remote Sensing, 58(1-2):19-30.

[9]Chiuderi, A., 1997. E.1-Neural Networks for Multi-Temporal and Multi-Sensor Data Fusion in Land Cover Classification. Proceedings of the 5th International Workshop on Time-Varying Image Processing and Moving Object Recognition, 4, Florence, Italy, p.147-152.

[10]Garzelli, A., Nencini, F., 2005. Interband structure modeling for pan-sharpening of very high-resolution multispectral images. Information Fusion, 6(3):213-224.

[11]Gillespie, A.R., Kahle, A.B., Walker, R.E., 1986. Color enhancement of highly correlated images I. decorrelation and HSI contrast stretches. Remote Sensing of Environment, 20(3):209-235.

[12]González-Audícana, M., Saleta, J.L., Catalán, R.G., García, R., 2004. Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 42(6):1291-1299.

[13]González-Audícana, M., Otazu, X., Fors, O., Alvarez-Mozos, J., 2006. A low computational-cost method to fuse IKONOS images using the spectral response function of its sensors. IEEE Transactions on Geoscience and Remote Sensing, 44(6):1683-1691.

[14]He, D.C., Li, W., Amani, M., 2004. A New Technique for Multi-Resolution Image Fusion. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA, 7:4901-4904.

[15]Janssen, L.L.F., Jaarsma, M.N., Linden, E.T.M., 1990. Integrating topographic data with remote sensing for land-cover classification. Photogrammetric Engineering and Remote Sensing, 56:1503-1506.

[16]Kratt, C., Calvin, W., Coolbaugh, M., 2006. Geothermal exploration with Hymap hyperspectral data at Brady-Desert Peak, Nevada. Remote Sensing of Environment, 104(3):313-324.

[17]Laporterie-Déjean, F., de Boissezon, H., Flouzat, G., Lefévre-Fonollosa, M.J., 2005. Thematic and statistical evaluations of five panchromatic/multispectral fusion methods on simulated PLEIADES-HR images. Information Fusion, 6(3):193-212.

[18]Lu, S.L., Shen, X.H., Zou, L.J., 2006. Land cover change in Ningbo and its surrounding area of Zhejiang Province, 1987~2000. Journal of Zhejiang University-SCIENCE A, 7(4):633-640.

[19]Mas, J.F., 2004. Mapping land use/cover in a tropical coastal area using satellite sensor data, GIS and artificial neural networks. Estuarine, Coastal and Shelf Science, 59(2):219-230.

[20]Nencini, F., Garzelli, A., Baronti, S., Alparone, L., 2007. Remote sensing image fusion using the curvelet transform. Information Fusion, 8(2):143-156.

[21]Nikolakopoulos, K.G., 2004. Comparison of Four Different Fusion Techniques for IKONOS Data. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA, 4:2534-2537.

[22]Ninomiya, Y., Fu, B.H., Cudahy, T.J., 2005. Detecting lithology with advanced spaceborne thermal emission and reflection radiometer (ASTER) multispectral thermal infrared “radiance-at-sensor” data. Remote Sensing of Environment, 99(1-2):127-139.

[23]Oguro, Y., Takeuchi, S., Suga, Y., Ogawa, H., Tsuchiya, K., 2003. Higher resolution images for visible and near infrared bands of Landsat-7 ETM+ by using panchromatic band. Advances in Space Research, 32(11):2269-2274.

[24]Pohl, C., Genderen, J.L., 1995. Image Fusion of microwave and Optical Remote Sensing Data for Map Updating in the Tropics. Proceedings of Image and Signal Processing for Remote Sensing, Paris, France, 2579:2-10.

[25]Pohl, C., Genderen, J.L., 1998. Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19(5):823-854.

[26]Ramadan, T.M., Kontny, A., 2004. Mineralogical and structural characterization of alteration zones detected by orbital remote sensing at Shalatein District, SE Desert, Egypt. Journal of African Earth Sciences, 40(1-2):89-99.

[27]Rokhmatuloh, Tateishi, R., Wikantika, K., Munadi, K., Aslam, M., 2003. Study on the Spectral Quality Preservation Derived from Multisensor Image Fusion Techniques between JERS-1 SAR and Landsat TM Data. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 6:3656-3658.

[28]Shi, W.Z., Zhu, C.Q., Tian, Y., Nichol, J., 2005. Wavelet-based image fusion and quality assessment. International Journal of Applied Earth Observation and Geoinformation, 6(3-4):241-251.

[29]Shimoni, M., Borghys, D., Heremans, R., Perneel, C., Acheroy, M., 2009. Fusion of PolSAR and PolInSAR data for land cover classification. International Journal of Applied Earth Observation and Geoinformation, 11(3):169-180.

[30]Simone, G., Farina, A., Morabito, F.C., Serpico, S.B., Bruzzone, L., 2002. Image fusion techniques for remote sensing applications. Information Fusion, 3(1):3-15.

[31]Smith, G.M., Wyatt, B.K., 2007. Multi-scale survey by sample-based field methods and remote sensing: a comparison of UK experience with European environmental assessments. Landscape and Urban Planning, 79(2):170-176.

[32]Suga, Y., 1992. Land use survey using remote sensing and geographical information systems. Advances in Space Research, 12(7):395-405.

[33]Swaminathan, V.L., Kamat, D.S., Rakshit, A.M., Chakraborty, D.K., Kurien, T.K., 1983. Application of remote sensing techniques in mineral resources survey—a case study pertaining to Singhbhum Shear Zone, Bihar, India. Advances in Space Research, 3(2):55-58.

[34]Tu, T.M., Su, S.C., Shyu, H.C., Huang, P.S., 2001. A new look at IHS-like fusion methods. Information Fusion, 2(3):177-186.

[35]Wald, L., 1999. Some terms of reference in data fusion. IEEE Transactions on Geoscience and Remote Sensing, 37(3):1190-1193.

[36]Wald, L., Rachin, T., Mangolini, M., 1997. Fusion of satellite images of different spatial resolutions: assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing, 63(6):691-699.

[37]Welch, R., Ehlers, M., 1987. Merging multi-resolution SPOT HRV and Landsat TM data. Photogrammetric and Remote Sensing, 53(3):301-303.

[38]Weydahl, D.J., 1993. Multitemporal Analysis of ERS-1 SAR Images over Land Areas. Proceedings of the 13th Annual IEEE International Geoscience and Remote Sensing Symposium, Tokyo, Japan, 3:1459-1461.

[39]Wilkinson, G.G., Folving, S., Kanellopoulos, I., McCormick, N., Fullerton, K., Mégier, J., 1995. Forest mapping from multi-source satellite data using neural network classifiers —an experiment in Portugal. Remote Sensing Reviews, 12(1-2):83-106.

[40]Wu, F., Wang, C., Zhang, W.G., Zhang, H., Wu, J., Liu, H., 2003. Fusion of Airborne Synthetic Aperture Radiometer and Landsat ETM+ Images. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 6:3899-3901.

[41]Yésou, H., Besnus, Y., Rolet, J., 1993. Extraction of spectral information from Landsat TM data and merger with SPOT panchromatic imagery-a contribution to the study of geological structures. ISPRS Journal of Photogrammetry and Remote Sensing, 48(5):23-36.

[42]Zhang, Y., Hong, G., 2005. An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images. Information Fusion, 6(3):225-234.

[43]Zhang, G.F., Shen, X.H., Zou, L.J., Li, C.J., Wang, Y.L., Lu, S.L., 2007. Detection of hydrocarbon bearing sand through remote sensing techniques in the western slope zone of Songliao basin, China. International Journal of Remote Sensing, 28(8):1819-1833.

[44]Zhang, G.F., Zou, L.J., Shen, X.H., Lu, S.L., Li, C.J., Chen, H.L., 2009. Remote sensing detection of heavy oil through spectral enhancement techniques in the western slope zone of Songliao Basin, China. AAPG Bulletin, 93(1):31-49.