Multi-spectrum image fusion algorithm based on weighted and improved wavelet transform

Zhiwen Wang, Shaozi Li, Qixian Cai, Songzhi Su, Meizhen Liu
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引用次数: 4

Abstract

A multi-spectrum image fusion algorithm with weighted bi-orthogonal self-adaptive wavelet transform is put forward in this paper, which can make up for defects that there are faintness of image details in multi-spectrum image fusion of lower contrast image. The self-adaptive method of wavelet coefficient local model maximum which is weighted is used to fuse the high frequency components and the syncretism adaptive method is also chosen in the course of fusing low frequency coefficient. The capability of multi-spectrum image fusion is evaluated by calculating mean grads of image. The experimental results show that the fusion rule of our proposed method is more effective.
基于加权和改进小波变换的多光谱图像融合算法
提出了一种加权双正交自适应小波变换的多光谱图像融合算法,弥补了低对比度多光谱图像融合中图像细节模糊的缺陷。采用加权的小波系数局部模型极大值自适应方法融合高频分量,融合低频分量时采用融合自适应方法。通过计算图像的平均梯度来评价多光谱图像融合的能力。实验结果表明,该方法的融合规则更为有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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