A novel medical image fusion with lαβ color transformation

For clinical application, the medical images play a vital role. The various multimodal medical images like MRI(magnetic resonance imaging), CT(computed tomography), PET(positron emission tomography), SPECT(single photon emission computed tomography) etc., represent various functional information of the body. The purpose of the proposed work is to acquire more information of the various clinical multi modal images in single image with good visual perception and more quality (called process of fusion). This paper proposes a novel image fusion with new color transformation. Non Subsampled Contourlet Transform (NSCT) is used in this work. At first, one of the RGB color images is transformed into lαβ color model. Later NSCT is applied on source images to obtain low & high frequency coefficients. Here, low frequency coefficients are processed using phase congruency model and high frequency coefficients are processed using Sum modified laplacian (SML) based directive contrast model. At last, the proposed method is compared with existing method [14]. The effectiveness of proposed method is is applied for assessing using various performance measures like normalized mutual information and structural similarities metrics.