Image Fusion and Change Detection Using Cohen – Daubechies – Feauveau (9/7) Transform

International Journal of Electronics and Communication Engineering

© 2019 by SSRG - IJECE Journal

Volume 6 Issue 11

Year of Publication : 2019

Authors : V.S. Priya Sumitha, R. Thangavel

10.14445/23488549/IJECE-V6I11P101

How to Cite?

V.S. Priya Sumitha, R. Thangavel, "Image Fusion and Change Detection Using Cohen – Daubechies – Feauveau (9/7) Transform," SSRG International Journal of Electronics and Communication Engineering, vol. 6,  no. 11, pp. 1-5, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I11P101

Abstract:

The surface of the world is dynamic every day due to the change in its features caused by nature and other means. The change detection of the world’s surface featuresis extremely necessary for understanding relationships and interactions between human and natural phenomena to produce higher cognitive processes. Satellite images will provide valuable information for disaster management like Floods, Earthquakes, Storm Surge, Landslides, Fires, Volcanic Eruptions, and Drought. The causes of the disaster and its assessment can be carried out using a multi-temporal approach that requires a set of images pre-damage and post-damage of the affected place, which is compared to spot the changes. However, the standard of the satellite images is not sensible to spot the changes. Therefore, the image fusion technique is implemented to enhance the image’s standard, and the differencing technique is used to spot the changes. Different image fusion algorithms are analyzed with the proposed method using Graphical User Interface in MATLAB. Performance of fusion is calculated based on PSNR, MSE, NCC, CC, SSIM, and the total processing time. The results demonstrate the fusion scheme’s effectiveness based on CDF (9/7) wavelet transform.

Keywords:

CDF (9/7), Change Detection, Image fusion, Multi-temporal Images

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