REGION-BASED IMAGE FUSION USING A COMBINATORY CHEBYSHEV-ICA METHOD

被引：0

作者：

Omar, Zaid ^{[1
]}

Mitianoudis, Nikolaos ^{[1
]}

Stathaki, Tania ^{[1
]}

机构：

[1] Imperial Coll London, Commun & Signal Proc Grp, Kensington SW7 2AZ, England

来源：

2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2011年

关键词：

Image and data fusion; Chebyshev polynomials; independent component analysis; region-based fusion;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

The aim of this paper is to provide an algorithm for image fusion which combines the techniques of Chebyshev polynomial (CP) approximation and independent component analysis (ICA), based on the regional information of input images. We present a region-based method that combines the merits of both techniques. It utilises segmentation to identify edges, texture and other important features in the input image and subsequently apply the different fusion methods according to regions. The proposed method exhibits better perceptual performance than individual CP and ICA fusion approaches especially in noise corrupted images.

引用

页码：1213 / 1216

页数：4

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