Abstract

This paper proposes the image fusion based on counterlet transform and discrete wavelet transform. The DWT and CT transform are used to extract the best features from different blur input images. The images are portioned based on dimensional reduction methods such as Laplacian pyramid and different coefficients from discrete wavelet transform to enhance the mean square error (MSE) and peak signal to noise ratio (PSNR) for exhibit the good appearance of output image i.e. image fusion. Hybrid DWT architecture has the advantage of lowers computational complexities and higher efficiencies. The algorithm is written in system MATLAB software. Image fusion based on contoulet transform and discrete wavelet transform gives better MSE and PSNR results as compared to existing methods.

Keywords: Counterlet transform, directional filter bank, and DWT.

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