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Communication Dans Un Congrès Année : 2010

Pansharpening with a decision fusion based on the local size information

Résumé

Pansharpening may be defined as the process of synthesizing multispectral images at a higher spatial resolution. Different pansharpening methods produce images with different characteristics. In the 2006 IEEE Data Fusion Contest, A\' -trous Wavelet Transform based pansharpening (AWLP) and Context Adaptive (CBD) pansharpening methods were declared as joint winners. While assessing the quantitative quality of the pansharpened images, it was observed that the two methods outperform each other depending upon the local content of the scene. Hence, it is interesting to develop a method which could produce results locally approximately similar to the best method, among the two pansharpening methods. In this paper we propose a method which selects either of the two methods for performing pansharpening on local regions, based upon the size of the objects. The results obtained demonstrate that the proposed method produces images with quantitative results approximately similar to the method which is better among the AWLP and CBD pansharpening methods.
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Dates et versions

hal-00578964 , version 1 (22-03-2011)

Identifiants

  • HAL Id : hal-00578964 , version 1

Citer

Bin Luo, Muhammad M. Khan, Thibaut Bienvenu, Jocelyn Chanussot. Pansharpening with a decision fusion based on the local size information. ICIP 2010 - 17th IEEE International Conference on Image Processing, Sep 2010, Hong Kong, Hong Kong SAR China. conference proceedings. ⟨hal-00578964⟩
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