Abstract
Remote sensing satellite images play an important role in many applications such as environment and agriculture lands monitoring. In such images the scene is usually observed with different modalities, e.g. wavelengths. Image Fusion is an important analysis tool that summarizes the available information in a unique composite image. This paper proposes a new transform domain image fusion (IF) algorithm based on a hierarchical vector hidden Markov model (HHMM) and the mixture of probabilistic principal component analysers. Results on real Landsat images, quantified subjectively and using objective measures, are very satisfactory.
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Flitti, F., Bennamoun, M., Huynh, D., Bermak, A., Collet, C. (2009). Probabilistic Satellite Image Fusion. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_50
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DOI: https://doi.org/10.1007/978-3-642-03767-2_50
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