Data fusion thanks to an improved morphological pyramid approach: comparison loop on simulated images and application to SPOT 4 data

To survey vegetation cover, obtaining reflectance temporal profiles is very important. Regularly and frequently acquired measurements are necessary to get "continuous" profiles. The SPOT4-VEGETATION and NOAA-AVHRR sensors fulfil these conditions. The major drawback is their coarse resolution of about 1 km. On the contrary, high spatial resolution sensors as SPOT 4-HRVIR (10 and 20 m), provide adequate images with a high probability of having only one kind of vegetation in one pixel. However, only a few images per year are available: this can't allow an accurate vegetation monitoring. Combining those two kinds of complementary sensors may provide efficient data for setting up temporal profiles. In this article a morphological pyramid approach is used to combine the high and coarse resolution data. In this paper, data fusion is based on the morphological pyramid principle in order to obtain the best filter.