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

机译:基于加权改进小波变换的多光谱图像融合算法

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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.
机译:本文提出了一种具有加权双正交自适应小波变换的多频谱图像融合算法,其可以弥补缺陷,即在较低对比度图像的多频谱图像融合中存在图像细节的微弱性。作为加权的小波系数局部模型最大值的自适应方法用于熔化高频分量,并且在融合低频系数的过程中也选择了汇总自适应方法。通过计算图像的平均级来评估多频谱图像融合的能力。实验结果表明,我们所提出的方法的融合规则更有效。

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