Log Gabor and wavelet-based transform for enhanced CT MRI image fusion

Image fusion is an important technique used in medical imaging to increase accuracy of medical diagnostics. This study will now present a hybrid approach for CT and MRI image fusion technique that uses Gaussian filtering and CLAHE to reduce noise, improve contrast, and boost multi-resolution capabilities. Wavelet Transform is used for reliable multi-resolution decomposition, while Log Gabor filters are applied to extract textural characteristics from images. Our method is comparable to conventional averaging (SSIM: 0.827, entropy: 6.68; PSNR: 28.31 dB) and demonstrates improved analysis capabilities in the hybridized image fusion process. The hybridized imaging strategy enhances considerer capabilities and creates new opportunities for further research in medical image fusion.