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基于梯度权重规则的IHS变换与小波变换结合算法 被引量:1

Algorithm combined of IHS transform and wavelet transform based on gradient weight rule
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摘要 针对多光谱图像与全色图像的融合,本文在认真分析了IHS变换、小波变换,以及基于梯度绝对值最大准则的IHS变换与小波变换结合算法的基础上,提出了一种基于梯度权重规则的改进算法。在使用小波变换融合多光谱图像I分量与全色图像时,计算二者高频细节分量的梯度作为权重,实现高频细节信息的融合;低频近似分量采用经验调节权系数的方式,运用加权和准则融合获得。融合所得新I′分量与之前多光谱图像IHS变换分离出的色度H和饱和度S进行逆变换,生成最终的融合图像。实验结果表明,该方法在保留多光谱图像光谱信息的基础上,有效地增强了融合图像的空间细节表现能力。 By analyzing HIS transform, wavelet transform, an improved image fusion method is presented based on gradient weight rule. While merging the high-frequency detail information of the panchromatic image and the I component of the multispectral image with WPT-based fusion method, the computation of high-frequency detail image's gradient is introduced into the process of selecting wavelet coefficient. The wavelet coefficient of different high-frequency detail images is added with different weights according to their gradient value. And the Low-frequency approximate images of the panchromatic image and the I component of the multispectral image are merged by experience coefficient method. Through inverse WPT, the new image I' component is obtained to replace the original I component of the multispectral image. Finally, the fusion result image is obtained by inverse HIS transform. The experimental result indicates that the improved method not only can enhance spatial detail information of the fusion result image largely, but also can preserve spectral information of the original multispectral image well.
出处 《光电工程》 EI CAS CSCD 北大核心 2007年第10期102-107,共6页 Opto-Electronic Engineering
关键词 IHS变换 小波变换 梯度权重规则 图像融合 HIS transform wavelet transform gradient weight rule image fusion
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