Merging Landsat and SPOT digital data using stochastic simulation with reference images

Júlia Carvalho 1, Jorge Delgado-García 2 and Amílcar Soares 1
1 Environmental Group of the Centre for Modelling Petroleum Reservoirs, CMRP/IST
Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Tel.: + 351 218 417 444; Fax: + 351 218 417 389
jcarvalho@ist.utl.pt; asoares@ist.utl.pt
2 Dpto. Ingeniería Cartográfica, Geodésica y Fotogrametria, Escuela Politécnica Superior, Univ. de Jaén
Campus de las Lagunillas, Edif. A-3. 23071 Jaén, España
Tel.: + 344 953 212 468; Fax: + 34 953 212 855
jdelgado@ujaen.es

Abstract
There is a wide range of systems providing digital satellite imagery with different spatial and spectral resolutions. But, unfortunately, these resolutions are in most cases opposite; i.e., the high-resolution sensors have low spectral resolution whereas the multiespectral sensors have good spectral resolution but bad spatial resolution making their use in detailed applications difficult. The problem is solved using digital image merging procedures. The main objective of these methods is to obtain synthetic images that combine the advantage of the high spatial resolution of one image with the high spectral resolution of another image. Ideally, the method used to merge data sets with high-spatial  resolution and high-spectral resolution should not distort the spectral characteristics of the high spectral resolution data. The classical methods of merging procedures (PCA, IHS, HPS, etc.) present several drawbacks. The objective of this paper is to present a geostatistical merging methodology based on direct sequential co- simulation with reference images (Carvalho et al., 2006). With the stochastic simulation one generates a high spatial resolution image with the characteristics of the of the higher spectral resolution image. It is an iterative inverse optimization procedure that tends to reach the matching of an objective function by preserving the spectral characteristics and spatial pattern, as revealed by the variograms, of the higher-spectral resolution images both in terms of descriptive statistics and band correlation coefficients. The method was applied to Landsat TM and SPOT-P images. The results were compared with the original Landsat image and the images provided by classical merging procedures.

Keywords: digital image merging method, geostatistics, stochastic simulation

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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