基于NSCT和小波变换的图像融合

Q. Miao, Jingjing Lou, Pengfei Xu
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引用次数: 8

摘要

提出了一种基于非次采样轮廓let变换和Bandelet变换的图像融合算法。作为两种不同的MGA工具,NSCT凭借其良好的多分辨率、位移不变性和高方向性等特点,可以给出图像中边缘和轮廓的渐近最优表示;Bandelet变换可以利用图像结构的几何规律性,在图像融合中有效地表示边缘等尖锐的图像过渡。本文提出了一种新的方法,将这两种变换结合到融合图像中。首先用NSCT将两幅源图像分解成不同的频率子带,然后用Bandelet变换进一步分解高频子带。其次,利用融合规则对两幅图像的高频子带进行融合,并利用Bandelet反变换对融合子带进行重构;最后,对低频子带和高频子带进行融合,利用逆NSCT得到融合图像。实验结果表明,与其他方法相比,基于该方法的融合结果包含更多的细节和更小的失真信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Fusion Based on NSCT and Bandelet Transform
A novel image fusion algorithm based on non-sub sampled contour let transform(NSCT) and Bandelet transform is proposed in this paper. As two different MGA tools, NSCT can give an asymptotic optimal representation of edges and contours in image by virtue of its characteristics of good multi-resolution, shift invariance, and high directionality, and Bandelet transform can take advantage of the geometrical regularity of image structure and represent sharp image transitions such as edges efficiently in image fusion. The new method, joint this two transforms to fuse image, is proposed in this paper. Firstly, two source images are decomposed into different frequency sub bands by NSCT, and then high frequency sub bands are further decomposed by Bandelet transform. Secondly", "the high frequency sub bands of the two images are fused with fusion rule and the fusion sub bands are reconstructed using inverse Bandelet transform. Finally, fusion low and high frequency sub bands and then the fused image is obtained by using inverse NSCT. Several different experiments are adopted to demonstrate that the fusion results based on the proposed method contain more details and smaller distortion information than any other methods does.
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