An improved multimodal medical image fusion scheme based on hybrid combination of nonsubsampled contourlet transform and stationary wavelet transform. Issue 2 (7th February 2019)

• Record Type: Journal Article
• Authors: Ramlal, Sharma Dileepkumar; Sachdeva, Jainy; Ahuja, Chirag Kamal; Khandelwal, Niranjan
• Is Part Of: International journal of imaging systems and technology. Volume 29:Issue 2(2019)
• Page Start: 146
• Page End: 160
• Publication Date: 2019-02-07
• Subjects: entropy of square of the coefficient -- medical image fusion -- nonsubsampled contourlet transform -- stationary wavelet transform -- weighted sum‐modified Laplacian; Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22310
• Languages: English
• ISSNs: 0899-9457

Abstract

Abstract: This research proposes an improved hybrid fusion scheme for non‐subsampled contourlet transform (NSCT) and stationary wavelet transform (SWT). Initially, the source images are decomposed into different sub‐bands using NSCT. The locally weighted sum of square of the coefficients based fusion rule with consistency verification is used to fuse the detailed coefficients of NSCT. The SWT is employed to decompose approximation coefficients of NSCT into different sub‐bands. The entropy of square of the coefficients and weighted sum‐modified Laplacian is employed as the fusion rules with SWT. The final output is obtained using inverse NSCT. The proposed research is compared with existing fusion schemes visually and quantitatively. From the visual analysis, it is observed that the proposed scheme retained important complementary information of source images in a better way. From the quantitative comparison, it is seen that this scheme gave improved edge information, clarity, contrast, texture, and brightness in the fused image.