Image Enhancement based on Fusion using 2D LPDCT and Modified PCA
C. Rama Mohan1, S. Kiran2, Vasudeva3, A. Ashok Kumar4
1C. Rama Mohan, Research Scholar, Department of CSE, VTU, Belgaum (Karnataka), India.
2S. Kiran, Department of CSE, YSR Engineering College of YVU, Proddatur (A. P), India.
3Vasudeva, Department of CSE, SMVITM, Bantakal, Udupi (Karnataka), India.
4A. Ashok Kumar, Department of Physics, YSR Engineering College, YVU Proddatur (A. P), India.
Manuscript received on 30 September 2019 | Revised Manuscript received on 12 November 2019 | Manuscript Published on 22 November 2019 | PP: 1482-1492 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F12640986S319/19©BEIESP | DOI: 10.35940/ijeat.F1264.0986S319
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Abstract: The images play a vital role in various fields of applications; medical field is the one, where images more widely used in diagnosis. Best image data analysis results if the quality of the image is high. To attain best image quality some popular techniques are available, among that image fusion is one of the technique, it enhances the information of the image by selecting and merging the significant information from two or more similar multi-focus images. Using the features of image fusion a new technique is proposed in this paper. In proposed technique, fusion of sources images with 2D Laplacian Pyramid Discrete Cosine Transformation (2D LP – DCT) and Modified Principal Component Analysis (MPCA). In this, two similar multi-focus images are considered, first, they undergone to 2D LP-DCT and then MPCA technique. The 2D LP-DCT enhances important image features, which are best utilized in image fusion and results good image quality. In Modified PCA, the concept of dimensionality reduction is used. The experimental results indicate that the suggested strategy can produce fused images with good visual quality and computational effectiveness than other state-of-the-art works.
Keywords: Laplacian Pyramid, Image Fusion, Multi-focus Images, DCT, Quality Evaluation Metrics, Image Quality, Modified Principal Component Analysis.
Scope of the Article: Image Security