• A Yaswanth
• N Akhil
• K DurgaPrasad
• B Satwika
• G V Vinod

Multispectral image fusion seeks to consolidate disparate spectral and spatial data into a single image by combining relevant data and eliminating noise. In this paper, we provide a Non-subsampled Contourlet Transform (NSCT)-based multispectral image fusion model that makes use of PCA, Phase congruency, directional contrast, and entropy. The proposed method utilises principal component analysis (PCA) for dimensionality reduction, fusion rules, and colour alterations to the multispectral input image. Different fusion rules are used for the high-pass and low-pass bands: The fusion rule is implemented using phase congruency for low-frequency coefficients, and with a combination of directed contrast and normalised Shannon entropy for high-frequency coefficients. The proposed model provides a more thorough scene characterisation than any other image, and this technique is utilised to cut down on a great deal of superfluous information. The advantages of the fusion reaction may be seen when compared with other modern fusion processes.

NSCT,PCA,CT/MRI,MRI/PET, SPECT/MRI

"Multi spectral medical image fusion using NSCT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.c9-c13, February-2023, Available :http://www.jetir.org/papers/JETIR2302202.pdf

"Multi spectral medical image fusion using NSCT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppc9-c13, February-2023, Available at : http://www.jetir.org/papers/JETIR2302202.pdf