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  • 标题:Comparison of Image Fusion Techniques: Spatial and Transform Domain based Techniques
  • 本地全文:下载
  • 作者:Veerpal Kaur ; Jaspreet Kaur
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2015
  • 卷号:4
  • 期号:5
  • 页码:12109-12112
  • 出版社:IJECS
  • 摘要:Image Fusion is a process of combining image details from a number of images into a single image, where the resultantfused image will have most of the details and is more informative and complete than any of the input images. Image fusiontechniques can increase the quality and populate the application domain of these data. In this paper we present a detailed study and surveyon some of the image fusion techniques for image fusion like, primitive fusion (Averaging Method, Select Maximum, and SelectMinimum), Discrete Wavelet transform based fusion, Principal component analysis (PCA) based fusion etc. Study and Comparisonof all the techniques helps to determine the better approach for its future research and implementation.
  • 关键词:Principal Component Analysis (PCA); Discrete Wavelet Transform (DWT); Mean Square Error (MSE); Normalized correlation;(NC); Peak signal to noise ratio (PSNR); Laplacian Fusion
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