This biomedical multimodal image fusion is an accurate and efficient procedure applied in human disease analysis by the clinicians. The significant objective of the biomedical image fusion is to incorporate all the content available from images to collect a single absolute expressive image which evolves a significant role in diagnosis, surgery and detection of diseases. An innovative hybrid fusion methodology is illustrated in this paper to fuse the biomedical multi-model images such as computed tomography (CT) and magnetic resonance imaging (MRI) of brain based on discrete wavelet transform (DWT) and principal component analysis (PCA) based on average gradient technique. The wavelet coefficients of frequency domain being estimated through the discrete wavelet transform (DWT) are mathematically fused using fusion rule and again fused in principal component analysis (PCA) procedure for accurate and efficient fusion. The biomedical fused image estimated by this technique are analyzed quantitatively by the various performance metrics and evaluated with the other existing algorithms for the advanced excellence investigation.
Volume 12 | Issue 8
Pages: 116-123
DOI: 10.5373/JARDCS/V12I8/20202453