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  • 标题:A Comparative Study of Classification of Image Fusion Techniques
  • 本地全文:下载
  • 作者:Sukhpreet Singh ; Rachna Rajput
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2014
  • 卷号:3
  • 期号:7
  • 页码:7350-7353
  • 出版社:IJECS
  • 摘要:Image fusion is a process by which complimentary details from multiple input images are integrated into a single image, where the output fused image provide more information and more suitable for the purpose of human visual perception. Several situations in image processing require high spatial and high spectral resolution in a single image, to achieve this one solution is image fusion. There are several image fusion techniques are present those can improve the quality of image and provide more extended depth detail. This paper presents classification of some of the image fusion techniques such as Spatial Domain Fusion(Averaging method, Brovey Method, Principal Component Analysis, IHS) and transform domain fusion(multiresolution, Laplacian pyramid, Curvlet transform based, Discrete Wavelet transform ). Comparison of all the techniques concludes the better approach for its future research.
  • 关键词:Image Fusion; Curvelet transform; Image quality assessment parameter; Pyramid Methods; Principal Component analysis(PCA)
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