Image Fusion Conspectus
Shalini Dutta1, Sudhakar S. Jadhav2
1Shalini Dutta, Master of Computer Applications (M.C.A), Lokmanya Tilak College of Engineering, Navi Mumbai, India.
2Professor Sudhakar S. Jadhav, Department of Computer Science, Lokmanya Tilak College of Engineering, Navi Mumbai, India.
Manuscript received on June 16, 2015. | Revised Manuscript received on June 29, 2015. | Manuscript published on July 05, 2015. | PP: 73-78 | Volume-5 Issue-3, July 2015. | Retrieval Number: C2653075315/2015©BEIESP
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©The Authors. Published By: 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: Technological advancements have brought extensive research in the field of Image Fusion. Image fusion is the process of amalgamation of relevant information from a set of input images into a single image which in turn is better informative, complete and accurate. This paper presents an overview of Image Fusion. The silhouette of the paper is anticipated to cover Image fusion right from its inception till the future research prospects. This covers the various fusion systems and techniques of image fusion such as Spatial Domain methods like Weighted Pixel Averaging, Select Maximum/Minimum, Principal Component Analysis (PCA), Frequency/Transform Domain methods like Pyramid Decomposition (Laplacian, FSD, Ratio, Gradient, Morphological), Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) based image fusion. A comparative study of various image fusion techniques and their analyzed results are enlisted. Vivacious applications of image fusion also are highlighted as well. The compendium is concluded with the analysis of better approach as a result of the comparative study and the future scope of research perseveres.
Keywords: Image Fusion, Discrete Wavelet Transform (DWT), Weighted Pixel Averaging, Select Maximum/Minimum, Principal Component Analysis (PCA), Pyramid Methods, Artificial Neural Network (ANN).