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An Improved Pca Fusion Method Based on Generalized Intensity–Hue–Saturation Fusion Technique


Authors



Abstract

Among various image fusion methods, principal component analysis (PCA) technique is capable of quickly merging the massive volumes of data. For IKONOS imagery, PCA can yield satisfactory “spatial” enhancement but may introduce spectral distortion, appearing as a change in colors between compositions of resembled and fused multi-spectral bands. To solve this problem, a fast improved PCA fusion method based on Intensity–Hue–Saturation Fusion Technique with Spectral Adjustment is presented. The experimental results demonstrate that the proposed approach can provide better performance than the original PCA method both in processing speed and image quality.


Keywords


Pages

Total Pages: 11
Pages: 1165-1175

DOI
10.1080/10798587.2008.10643320


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Published

Volume: 18
Issue: 8
Year: 2012

Cite this document


References

Jin jun, Wavelet-based Remote Sensing Image Fusion with PCA and Feature Product, Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference, 2006, 2053 — 2057 .

Haixia Liu, Comparison of Data Fusion Techniques for Beijing-1Micro-Satellite Images, Urban Remote Sensing Joint Event, 2009 .

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

TWO YEAR CITATIONS PER DOCUMENT (SJR DATA): 0.993 (2018)
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."





Journal: 1995-Present


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