ABSTRACT
Image fusion is the process of merging two images of the same scene to form a single image with as much information as possible. Image fusion is important in many different image processing fields such as satellite imaging, remote sensing and medical imaging. The study in the field of image fusion has evolved to serve the advance in satellite imaging and then, it has been extended to the field of medical imaging. Several fusion algorithms have been proposed extending from the simple averaging to the curvelet transform. The wavelet fusion algorithm has succeeded in both satellite and medical image fusion applications. The basic limitation of the wavelet fusion algorithm is in the fusion of curved shapes. Thus, there is a requirement for another algorithm that can handle curved shapes. So, the application of the curvelet transform for curved object image fusion would result in better fusion efficiency. This project introduces the Curvelet Transform and uses it to fuse images. The experiments show that the method could extract useful information from source images to fused images so that clear images are obtained. The main objective of medical imaging is to obtain a high resolution image with as much details as possible for the sake of diagnosis. MR and the CT techniques are medical imaging techniques. Both techniques give special sophisticated characteristics of the organ to be imaged. So, it is expected that the fusion of the MR and the CT images of the same organ would result in an integrated image of much more details. Due to the limited ability of the wavelet transform to deal with images having curved shapes, the application of the curvelet transform for MR and CT image fusion is presented. This project is developed in matlab.
PROJECT OUTPUT
PROJECT DEMO VIDEO
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