文章基本信息

标题：Enhanced Singular Value Decomposition based Fusion for Super Resolution Image Reconstruction
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作者：K. Joseph Abraham Sundar ; V. Vaithiyanathan ; M. Manickavasagam 等
期刊名称：Defence Science Journal
印刷版ISSN：0976-464X
出版年度：2015
卷号：65
期号：6
页码：459-465
语种：English
出版社：Defence Scientific Information & Documentation Centre
摘要：The singular value decomposition (SVD) plays a very important role in the field of image processing for applications such as feature extraction, image compression, etc. The main objective is to enhance the resolution of the image based on Singular Value Decomposition. The original image and the subsequent sub-pixel shifted image, subjected to image registration is transferred to SVD domain. An enhanced method of choosing the singular values from the SVD domain images to reconstruct a high resolution image using fusion techniques is proposesed. This technique is called as enhanced SVD based fusion. Significant improvement in the performance is observed by applying enhanced SVD method preceding the various interpolation methods which are incorporated. The technique has high advantage and computationally fast which is most needed for satellite imaging, high definition television broadcasting, medical imaging diagnosis, military surveillance, remote sensing etc.
关键词：Singular value decomposition, image fusion, super resolution, image registration, interpolation