An Efficient Image Enhancement Technique using Stationary Wavelet Transform Based Image Fusion
R. Adaline Suji1, D. Bright Anand2, R. Lenin Babu3
1R. Adaline Suji, Department of Computer Science and Engineering, Kalaignar Karunanidhi Institute of Technology, Coimbatore, (Tamil Nadu), India.
2D. Bright Anand, Department of Electronics and Communication Engineering, VSB Engineering College, (Tamil Nadu), India.
3R. Lenin Babu, Data Scientist and Artificial Intelligence Lead, ConverSight.ai, Coimbatore, (Tamil Nadu), India.
Manuscript received on 12 April 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 2012-2017 | Volume-8 Issue-1, May 2019 | Retrieval Number: F2419037619/19©BEIESP
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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: As far as the image processing area is concerned it is observed that it is comprised of various subfields, one such is the image fusion sub field. The devised responsibility of the Image fusion subfield is that it is expected to aggregate the various images of a particular scene together, this obtained final image has been found to provide additional information regarding the concerned scene and is further found to resolve the ambiguities in the selected input images. Another form of image fusion technique is the multi-sensor image fusion technique, in this technique the various images of a particular scene have been found to be obtained from different sensors possessing different resolution ranges. The next form of image fusion technique is the multi-focus image fusion technique, here the images pertaining to a particular scene would be collected from the same sensor and these images when aggregated together would result in the formation of an image that essentially comprises of all the objects that are in focus. Two different types of domains have been observed to exist in the image processing zone, these are known as the spatial and the transformed forms of domains, it is in these domains that the image fusion procedures would essentially take place. The procedure accomplished in the spatial domain is that the contained pixel values would be directly adopted into the fusion procedure, on the other hand in the transformed domain the input images would be initially converted by means of incorporating the wavelet decomposition mechanism or the pyramid decomposition strategy so as to exploit the available contents at various scales or multi-resolutions.
Index Terms: Principal Component Analysis, Discrete Wavelet Transform, Image fusion.
Scope of the Article: Image analysis and Processing