NDLI: Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition

Content Provider	Springer Nature Link
Author	Shah, Parul Merchant, Shabbir N. Desai, Uday B.
Copyright Year	2011
Abstract	Image fusion has been receiving increasing attention in the research community with the aim of investigating general formal solutions to a wide spectrum of applications. The objective of this work is to formulate a method that can efficiently fuse multifocus as well as multispectral images for context enhancement and thus can be used by different applications. We propose a novel pixel fusion rule based on multiresolution decomposition of the source images using wavelet, wavelet-packet, and contourlet transform. To compute fused pixel value, we take weighted average of the source pixels, where the weight to be given to the pixel is adaptively decided based on the significance of the pixel, which in turn is decided by the corresponding children pixels in the finer resolution bands. The fusion performance has been extensively tested on different types of images viz. multifocus images, medical images (CT and MRI), as well as IR − visible surveillance images. Several pairs of images were fused to compare the results quantitatively as well as qualitatively with various recently published methods. The analysis shows that for all the image types into consideration, the proposed method increases the quality of the fused image significantly, both visually and quantitatively, by preserving all the relevant information. The major achievement is average 50% reduction in artifacts.
Starting Page	95
Ending Page	109
Page Count	15
File Format	PDF
ISSN	18631703
Journal	Signal, Image and Video Processing
Volume Number	7
Issue Number	1
e-ISSN	18631711
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-03-22
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image fusion Multiresolution decomposition Multifocus/Multispectral images Context enhancement Signal, Image and Speech Processing Image Processing and Computer Vision Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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