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A Comparative Analysis of Wavelet Transform & PCA Image Fusion Techniques
Rakesh Aditya Mitra Hirve
This paper describes the comparison between Principal Component Analysis (PCA) and Wavelet Transform image fusion technique. Many different image fusion techniques have been developed but more efficient and robust methods are needed. In remote sensing applications, the increasing availability of space borne sensors gives a motivation for different image fusion algorithms. Several situations in image processing require high spatial and high spectral resolution in a single image. Most of the available equipment is not capable of providing such data convincingly. Image fusion techniques allow the integration of different information sources. The fused image can have complementary spatial and spectral resolution characteristics. However, the standard image fusion techniques can distort the spectral information of the multispectral data while merging.
Keywords- Image Fusion, Wavelet Transform, Principal of Component Analysis
Unique Identification Number - IJEDR1402183Page Number(s) - 2437-2442Pubished in - Volume 2 | Issue 2 | June 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Rakesh Aditya Mitra Hirve,   "A Comparative Analysis of Wavelet Transform & PCA Image Fusion Techniques"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 2, pp.2437-2442, June 2014, Available at :http://www.ijedr.org/papers/IJEDR1402183.pdf