计算机工程与应用2012，Vol.48Issue(8)：211-213,3.DOI:10.3778/j.issn.1002-8331.2012.08.060
基于PCA的拉普拉斯金字塔变换融合算法研究
PCA-based Laplacian pyramid in image fusion
摘要
Abstract
This paper explains the theory and method of image fusion based on principal component analysis of the Laplacian pyramid. The Laplacian image fusion scheme begins by constructing Laplacian pyramids for each source image, and then for the high frequency part it uses the Principal Component Analysis (PCA) fusion method, for the low frequency part it uses the average gradient method. Finally, the end fused image is obtained by inverse Laplacian pyramid transform. By analyzing the fusion image with visible and infrared image, and image fusion of different focal images, the experimental results show that this algorithm can produce high-contrast fusion images that are clearly more appealing and have greater useful information content than the PCA and the Laplace image fusion.关键词
图像融合/拉普拉斯金字塔/主元分析/平均梯度Key words
image fusion/ Laplacian pyramid/ Principal Component Analysis (PCA)/ average gradient分类
信息技术与安全科学引用本文复制引用
马先喜,彭力,徐红..基于PCA的拉普拉斯金字塔变换融合算法研究[J].计算机工程与应用,2012,48(8):211-213,3.基金项目
国家自然科学基金(No.60973095) （No.60973095）
