Advanced Multifocus Image Fusion algorithm using FPDCT with Modified PCA
C. Rama Mohan1, S. Kiran2, A. Ashok Kumar3
1C. Rama Mohan, Research Scholar, Department of CSE, VTU, Belgaum, Karnataka, India.
2Dr S. Kiran, Department of CSE, YSR Engineering College of YVU, Proddatur, A. P., India.
3Dr A. Ashok Kumar, Department of Physics, YSR Engineering College of YVU, Proddatur, A. P., India.
Manuscript received on November 13, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 175-184 | Volume-9 Issue-2, December 2019. | Retrieval Number: A5312119119/2019©BEIESP | DOI: 10.35940/ijitee.A5312.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Frequency Partitioning, Image Fusion, Modified PCA, Multi-Focus Images, DCT, Quality Evaluation Metrics, Comparative Analysis, Image Quality
Scope of the Article: Image analysis and Processing