IMAGE FUSION USING WAVELET AND CURVELET TRANSFORMS

Abstract

This paper presents wavelet and curvelet transform based approach for the fusion of digital image, magnetic resonance (MR) and computed tomography (CT) images. We looked at the selection principles about low and high frequency coefficients according to different frequency domain after Wavelet and the Curvelet Transform. In choosing the low-frequency and high frequency coefficients, the concept of local area variance an d window property of pixels respectively.Some attempts have been proposed for the fusion of MR and CT images using the wavelet transform. The objective of the fusion of an MR image and CT images of the same organ is to obtain a single imag e containing as much information as possible about that organ for diagnosis . Since medical images have several objects and curved shapes, it is expected that the curvelet transform would be better in their fusion. The simulation results show the superiority of the curvelet transform to the wavelet transform in the fusion of digital image an d MR and CT images from entropy, correlation coefficients and the RMS error points of view.