基于改进引导滤波和量子遗传算法的图像融合

李晓玲; 聂祥飞; 黄海波; 张月

doi:doi:10.3969/j.issn.1671-637x.2020.02.009

电光与控制, 2020, 27 (2): 40, 网络出版: 2020-05-12

基于改进引导滤波和量子遗传算法的图像融合

An Image Fusion Method Based on Improved Guided Filtering and Quantum Genetic Algorithm

论文大纲

李晓玲聂祥飞黄海波张月

作者单位

重庆三峡学院电子与信息工程学院,重庆 404100

图像处理图像融合引导滤波量子遗传算法小波变换 image processing image fusion guided filtering quantum genetic algorithm wavelet transform

摘要

为了有效解决图像融合中存在的光谱失真和空间细节信息缺失问题,提出一种基于改进引导滤波和量子遗传算法的图像融合方法。首先对多光谱图像进行上采样,并采用改进引导滤波对全色图像进行拟合处理,然后选用量子遗传算法对新的全色图像进行优化。依据小波变换法分别对多光谱图像和全色图像展开分解,选取高频部分进行加权平均融合,低频部分采用像素取大原则,最后通过小波逆变换得到融合图像。实验结果表明,改进方法能够有效提升图像的平均梯度、信息熵等指标,使得融合图像的光谱失真现象得到改善,边缘细节信息得到增强,视觉效果良好。

Abstract

To solve the problems of spectral distortion and lack of spatial details in image fusion, an image-fusion approach was proposed based on the improved guided filtering and quantum genetic algorithm.Firstly, up-sampling operation was used in multi-spectral image, and the panchromatic image was fitted by the improved guided filtering.Secondly, the new panchromatic image was optimized by using quantum genetic algorithm.Next, the multi-spectral image and panchromatic image were decomposed by wavelet transform.Then, weighted average was made to the high-frequency part, and the principle of selecting the maximum-pixel was used to the low-frequency part.Finally, the fusion image was reconstructed by adopting the inverse wavelet transformation.Experimental results show that the improved method effectively increases such image indicators as average gradient and information entropy, which can enhance the details and spectral information in image fusion, and get better visual effect.

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李晓玲, 聂祥飞, 黄海波, 张月. 基于改进引导滤波和量子遗传算法的图像融合[J]. 电光与控制, 2020, 27(2): 40. LI Xiaoling, NIE Xiangfei, HUANG Haibo, ZHANG Yue. An Image Fusion Method Based on Improved Guided Filtering and Quantum Genetic Algorithm[J]. Electronics Optics & Control, 2020, 27(2): 40.

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