부산대학교 도서관

A novel hybrid fusion scheme is proposed by employing non-subsampled shearlet transform (NSST) and stationary wavelet transform (SWT). In the preliminary stage, multimodal input images are putrefied comprehensively by NSST. The regional energy as an activity parameter is used to fuse the high-frequency sub-band coefficients of NSST. The approximation sub-band of NSST is fused using SWT. The maximum entropy of the squared coefficients and regional energy as the activity parameters are employed to fuse the LF and HF sub-bands of SWT, respectively. This step is explicitly performed for preserving contrast, edges, texture and brightness information within the image. The final output is taken by employing the inverse NSST. The research is verified both qualitatively and quantitatively from the fused images. It is seen that the suggested methodology obtained enriched results of the textural details such as divergence, boundaries, consistency and brightness of any of the brain intracranial masses (tumor or stroke or haemorrhage or even fungal infection). It is further observed that the morphology of the associated intracranial mass and the minimum path distance during invasive surgery along with the bone are prerequisites for the radiologist and are better depicted by the present method (as per the radiologist's perception). The fusion performance parameters of the suggested technique are related to seven existing methods. The quantitative evaluation of the proposed algorithm is done using mutual information, edge information index, entropy, standard deviation and mean. The parametric values obtained in any of the publicly available datasets or real-time datasets gave assuring outcomes. [ABSTRACT FROM AUTHOR]