A new image fusion algorithm based on second generation wavelet transform

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI:10.1109/CINC.2010.5643811

Bin Zhang, Yongguo Zheng, Weiqi Fang, Li-min Cui

{"title":"A new image fusion algorithm based on second generation wavelet transform","authors":"Bin Zhang, Yongguo Zheng, Weiqi Fang, Li-min Cui","doi":"10.1109/CINC.2010.5643811","DOIUrl":null,"url":null,"abstract":"A novel image fusion algorithm based on wavelet lifting scheme is presented. The lifting scheme is a new idea of constructing wavelets and has several unique advantages over conventional convolution-based wavelet transform. It allows for an in-place implementation of wavelet transform and reduces computation time and memory requirement greatly. So in this fusion algorithm, the lifting wavelet transform is employed to decompose and reconstruct images to realize fast image fusion. Meanwhile, a new local feature-based fusion rule is put forward to improve fusion quality and extract all significant features from multi-source images. Extensive experiments on the fusion of registered SPOT Panchromatic/multi-spectral images, multi-focus digital camera images,and medical MRI/CT images have been performed. Finally, visual judgment and several objective evaluation criterions are taken as the means of assessing fusion performance. The experimental results show that the new approach is very effective and is able to fuse multi-source images.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

Abstract

A novel image fusion algorithm based on wavelet lifting scheme is presented. The lifting scheme is a new idea of constructing wavelets and has several unique advantages over conventional convolution-based wavelet transform. It allows for an in-place implementation of wavelet transform and reduces computation time and memory requirement greatly. So in this fusion algorithm, the lifting wavelet transform is employed to decompose and reconstruct images to realize fast image fusion. Meanwhile, a new local feature-based fusion rule is put forward to improve fusion quality and extract all significant features from multi-source images. Extensive experiments on the fusion of registered SPOT Panchromatic/multi-spectral images, multi-focus digital camera images,and medical MRI/CT images have been performed. Finally, visual judgment and several objective evaluation criterions are taken as the means of assessing fusion performance. The experimental results show that the new approach is very effective and is able to fuse multi-source images.

查看原文本刊更多论文

基于第二代小波变换的图像融合新算法

提出了一种基于小波提升方案的图像融合算法。提升方案是一种构造小波的新思路，与传统的基于卷积的小波变换相比，具有许多独特的优点。它允许小波变换的就地实现，大大减少了计算时间和内存需求。因此，在该融合算法中，采用提升小波变换对图像进行分解和重构，实现图像的快速融合。同时，提出了一种新的基于局部特征的融合规则，以提高融合质量，并从多源图像中提取所有重要特征。对配准的SPOT全色/多光谱图像、多焦数码相机图像和医学MRI/CT图像进行了大量的融合实验。最后以视觉判断和若干客观评价标准作为评价融合性能的手段。实验结果表明，该方法能够有效地融合多源图像。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2010 Second International Conference on Computational Intelligence and Natural Computing

自引率

0.00%

发文量