东篱科研大数据发现系统（DRDS）

位置：成果数据库 > 期刊 > 期刊详情页

改进的Shearlet变换耦合频率特征的图像融合算法

ISSN号：1001-3563
期刊名称：《包装工程》
时间：0
分类：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
作者机构：[1]重庆城市职业学院,重庆402160, [2]电子科技大学,成都610000
相关基金：国家自然科学基金（61001032）; 重庆市2014年度科技成果转化重点研究资助基金（2015-ZJ-006）

关键词：图像融合, ST-NSWT, 区域能量, 频率特征, 区域平均梯度, image fusion, ST-NSWT, regional energy, frequency characteristics, regional average gradient

中文摘要：

目的解决当前图像融合算法大都直接在图像的像素灰度空间上进行融合,导致融合图像存在视觉效果差及算法鲁棒性不强等问题。方法文中提出改进的Shearlet变换耦合频率特征的多聚焦图像融合算法。将Shearlet变换（ST）和非下采样小波变换（NSWT）进行融合,形成改进的Shearlet变换（ST-NSWT）对源图像分解,获取图像的低、高频子带系数;构建区域能量模型,对源图像之间的低频子带系数进行相关性度量,完成低频子带的融合;对高频子带的频率特征进行分析,建立方差模型、平均梯度模型、空间频率模型,分别对源图像的灰度相关性、清晰度相关性及活跃度相关性进行测量,完成高频子带的融合,最后通过ST-NSWT逆变换,输出融合图像。结果与当前多聚焦图像融合算法相比,文中算法融合的图像能较好地保留更多的细节及边缘信息,使融合图像具备更佳的视觉效果。结论所提算法具有更好的融合质量,可用于遥感探测与包装印刷检测等领域。

英文摘要：

The work aims to solve the defect such as poor fusion image visual effect and low robustness induced by mostly achieving the image fusion on the pixel gray space of current image fusion algorithm. A new multi-focus image fusion algorithm based on improved shearlet transform coupling frequency characteristic was proposed in this paper. Firstly, the shearlet transform（ST） and the non-subsample wavelet transform（（NSWT）） were fused to form the improved shearlet transform（ST-NSWT）, and the ST-NSWT transform was used to decompose the source image to obtain the low and high frequency subband coefficients of the image. Then the regional energy model was constructed to measure the dependency between the low frequency subband coefficients of the source images, and to complete the fusion of low frequency subbands. Finally, through analysis on the frequency characteristics of high frequency subbands, the variance model, the average gradient model and the spatial frequency model were established to measure the gray correlation, resolution correlation and activeness correlation of the source image, so as to complete the fusion of high frequency subbands, and finally the fuse image was accomplished by inverse ST-NSWT transform. Compared with the current multi-focus image fusion algorithm, the proposed algorithm could preserve more details and edge information in a better way, which makes the fusion image have better visual effect. The proposed algorithm has better fuse quality and it can be used in such fields as remote sensing and packaging printing detection.

同期刊论文项目