Publication

Abstract : Multimodal fusion images minimize redundancy and increase the required data from the input imagery of various medical imagery sensors. The first and foremost goal is to establish a single fused image that could be more useful for successful clinical research. This work introduces a combination of two phases of hybrid processes, such as the SWTPCA and the One Dimensional-Discrete Wavelet Transform (1D-DWT) fusion of DWTPCA. The Laplacian based 1D-DWT is hybridized with combinations of WT (Wavelet Transform) and PCA (Principal Component Analysis). In this work, proposed two different hybrid algorithms, that are discussed in various sections of this paper. PCA fuses the approximation components to reduce the redundancy of both source images and to improve SWT's limit on non-directionality. To enhance the visual clarity of the image, the information components are fused with the Sum Modified Laplacian (SML). The suggested approach has been demonstrated by many sets of medical images in real-time. The paper demonstrates comparative assessments based on subjective and objective evaluation.