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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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摘要

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 multispectrum 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 multispectrum 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:提出了一种采用加权双正交自适应小波变换的多光谱图像融合算法,可以弥补低对比度图像多光谱图像融合中图像细节模糊的缺陷。采用加权小波系数局部模型最大值的自适应方法融合高频分量,并在融合低频系数的过程中选择了合声自适应方法。通过计算图像的平均灰度来评估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。

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