Image fusion has been performed and reported in this paper for multi-focused images using Frequency Partition Discrete Cosine Transform (FP-DCT) with Modified Principal component analysis (MPCA) technique. The image fusion with decomposition at fixed levels may be treated as a very critical rule in the earlier image processing techniques. The frequency partitioning approach was used in this study to select the decomposition levels based on the pixel intensity and clarity. This paper also presents the modified PCA technique which provides dimensionality reduction. The wide range of quality evaluation metrics was computed to compare the fusion performance on the five images. Different techniques such as PCA, wavelet transforms with PCA, Multiresolution Singular Value Decomposition (MSVD) with PCA, Multiresolution DCT (MRDCT) with PCA, Frequency partitioning DCT (FP-DCT) with PCA were computed for comparison with the proposed FP-DCT Modified PCA (MPCA) technique. Images obtained after fusion process obtained by the method proposed shows enhanced visual quality, negligible information loss and discontinuities in the image than compared to other state of the art methods.
Advanced Multifocus Image Fusion algorithm using FPDCT with Modified PCA
