Abstract
Image fusion’s goal is to merge material from multiple images of the same scene into a single image that preserves the essential and required features of each original image. Today, with the rapid development of high-tech and modern instrumentation, medical imaging has become a vital component of a wide range of applications including diagnosis, research, and treatment. Medical picture fusion is the principle to enhance image quality by fusing pictures obtained from different imaging instruments such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and computed tomography (SPECT) with single photon emission. SPECT contains the details about the functioning and blood flow of our tissues and organs for medical diagnosis. Magnetic Resonance Image (MRI) offers stronger, more distortion information on soft tissue. In this case, just one type of image may not be enough to provide the physicians with accurate clinical requirements. The fusion of the multimodal medical images is therefore needed. This paper introduces an image fusion approach that is based on discrete wavelet transformation. 2-Dimensional DWT for decomposing an image. The fusion performance is evaluated using Mutual Information (MI) and Correlation of Fused Image and Reference Image.
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