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给出了一种基于小波变换的图像融合方法,对小波分解后的低频分量通过度量其图像块空间频率和对比度来确定融合图
像的低频分量,对分解后得到的高频分量,选择高频系数时,基于绝对值最大的原则,并对选择结果进行一致性验证,最后重构得
到融合图像。从仿真结果可以看出,给出的方法很好地保留了多幅原图像的有用信息,融合图像清晰度和对比度都较好,是一种有
效的图像融合算法-This paper presents a wavelet-based image fusion method, after the wavelet decomposition of the low frequency components through the measurement of its image block spatial frequency and contrast to determine the integration of low-frequency component images of decomposition after the high-frequency component, select the high-frequency coefficient and, based on the principle of the absolute value of the largest, and choose to verify consistency of results, and finally remodeling be fused image. From the simulation results can be seen that the method gives a good number of the original image to retain the useful information, integration of image sharpness and contrast are better, is an effective image fusion algorithm
像的低频分量,对分解后得到的高频分量,选择高频系数时,基于绝对值最大的原则,并对选择结果进行一致性验证,最后重构得
到融合图像。从仿真结果可以看出,给出的方法很好地保留了多幅原图像的有用信息,融合图像清晰度和对比度都较好,是一种有
效的图像融合算法-This paper presents a wavelet-based image fusion method, after the wavelet decomposition of the low frequency components through the measurement of its image block spatial frequency and contrast to determine the integration of low-frequency component images of decomposition after the high-frequency component, select the high-frequency coefficient and, based on the principle of the absolute value of the largest, and choose to verify consistency of results, and finally remodeling be fused image. From the simulation results can be seen that the method gives a good number of the original image to retain the useful information, integration of image sharpness and contrast are better, is an effective image fusion algorithm
相关搜索: 图像融合
基于小波变换的图像融合
信息融合
fusion
of
images
spatial
frequency
wavelet
fusion
method
for
contrast
融合
块
contourlet
wavelet
image
fusion
小波
图像融合
基于小波变换的图像融合
信息融合
fusion
of
images
spatial
frequency
wavelet
fusion
method
for
contrast
融合
块
contourlet
wavelet
image
fusion
小波
图像融合
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一种基手小波变换的图像融合新算法.pdf