In this paper, a new extension of Bidimensional Empirical Mode Decomposition (BEMD) based on the median filtering is presented. The new scheme is compared with the traditional Empirical Mode Decomposition (EMD) and Fast and Adaptive Bidimensional EMD (FABEMD) techniques. The new scheme manifests to be superior to both of them in image enhancement and particularly in edge enhancement. The comparison is performed, objectively, using the measure of enhancement (EME) and also visually. Furthermore, we show that by applying different thresholds in stopping condition for each Intrinsic Mode Function (IMF), we can derive more accurate IMFs.
In this paper, a speckle noise reduction method is presented. The proposed method is based on a combination of nonlinear anisotropic diffusion filter and Ensemble Empirical Mode Decomposition (EEMD) technique. It incorporates the advantages of the two techniques. The experimental results on the images speckled by various levels of noise show that the proposed method is able to significantly improve the performance of nonlinear anisotropic diffusion filter. Furthermore, it outperforms several well-known speckle reduction algorithms in terms of noise removal as well as image features preservation.
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