Optimum threshold parameter estimation of bidimensional empirical mode decomposition using fisher discriminant analysis for speckle noise reduction

Abstract EN

Now a days Empirical Mode Decomposition (EMD) is an important tool for image analyzing.

Optimizing threshold value of Bidimensional Intrinsic Mode Function (BIMF) is one of the important tasks in speckle noise reduction in the Bidimensional Empirical Mode Decomposition (BEMD) domain.

Without proper selection of threshold value image information may be lost, which is unwanted.

In this paper we proposed optimum threshold parameter using Fisher Discriminant Analysis (FDA) for determining the optimum threshold value of the Intrinsic Mode Functions (IMF) for the best speckle noise reduction.

In the mean time, we used the optimal threshold value for separating the higher frequency signal from BIMF to calculate the mean of these separated signals for alleviating speckle noise.

It also preserves edges without loss of important image information.

The method is compared with the several other classical thresholding methods on variety of images and the experimental results confirm significant improvement over existing methods.