范晖,夏清国,乌伟.区域特征耦合DS证据理论的图像融合算法[J].包装工程,2017,38(5):183-189.
FAN Hui,XIA Qing-guo,WU Wei.Image Fusion Algorithm Based on Regional Characteristic Coupled DS Evidence Theory[J].Packaging Engineering,2017,38(5):183-189. |
| 区域特征耦合DS证据理论的图像融合算法 |
| Image Fusion Algorithm Based on Regional Characteristic Coupled DS Evidence Theory |
| 投稿时间：2016-09-05 修订日期：2017-03-10 |
| DOI： |
| 中文关键词: 图像融合 二代Curvelet变换 最大值融合规则 DS证据理论融合规则 区域相关性 |
| 英文关键词: image fusion 2nd generation Curvelet transform maximum fusion rule fusion rule of DS evidence theory regional correlation |
| 基金项目:国家自然科学基金（51405382）；陕西省教育厅专项科研计划（14JK2163） |
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| 中文摘要: |
| 目的 提高融合图像视觉质量。方法 提出区域多特征与改进的DS证据理论规则的聚焦图像融合算法。首先，引入二代Curvelet变换，对源图像进行分解，获取图像的粗尺度系数、细尺度系数；然后，根据区域中粗尺度系数的绝对值，构造最大值融合规则，完成粗尺度系数的融合；再联合区域方差、信息熵以及区域能量等特征，提取细尺度层的区域特征，并通过定义概率约束条件，改进DS证据理论的融合规则，增强DS合成规则的可信度，对图像的细尺度系数进行有效融合，使得融合图像保留更多的细节信息；最后，通过逆Curvelet变换完成图像的融合。结果 与当前的图像融合算法相比，在对聚焦图像融合时，文中算法的融合图像具有更丰富的细节信息，其视觉质量更高，且融合时耗较短。结论 所提算法考虑了像素之间的互相关性，进一步优化了图像融合质量，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 improve the visual quality of fusion image. The focus image fusion algorithm with regional multi-features and improved DS evidence theory rule is proposed. First of all, the 2nd generation Curvelet transform was introduced to decompose source image and obtain the coarse scale coefficients and fine scale coefficients. Then, according to the absolute values of the coarse scale coefficients in the selected region, the maximum fusion rule was constructed to fuse the coarse scale coefficients. In combination with such features as regional variance, information entropy and regional energy, the regional features of the fine scale layers were extracted. Moreover, by defining the probability constraints, the fusion rule of DS evidence theory was improved, the credibility of DS fusion rule was enhanced, and the fine scale coefficients of the image were effectively fused, so that the fuse image could preserve more details. Finally, the image fusion was completed by inverse Curvelet transform. The simulation results showed that, compared with the current image fusion algorithm, the fuse image of the proposed algorithm can preserve more abundant details and have better visual effect and its fusion is less time-consuming. It is concluded that the proposed algorithm has taken into account the cross correlation between pixels and further optimized the image fuse quality, and it can be applied to such fields as remote sensing and package printing detection. |
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