基于SHT域TAM-SCM与焦聚区域检测的图像融合算法 -- 西北工业大学学报,2019,37(1):114-121
论文:2019,Vol:37,Issue(1):114-121
引用本文:
王峰, 程咏梅, 李辉. 基于SHT域TAM-SCM与焦聚区域检测的图像融合算法[J]. 西北工业大学学报
WANG Feng, CHENG Yongmei, LI Hui. Image Fusion Algorithm of Focal Region Detection and TAM-SCM Based on SHT Domain[J]. Northwestern polytechnical university

基于SHT域TAM-SCM与焦聚区域检测的图像融合算法
王峰, 程咏梅, 李辉
西北工业大学 自动化学院, 陕西 西安 710129
摘要:
针对聚焦图像融合过程中细节信息的选取和振铃效应问题,提出了一种基于剪切波(shearlet,SHT)域3种活跃量测(three activity measures,TAM)激发脉冲皮发神经元模型(spiking cortical model,SCM)的多聚焦图像融合新算法。首先,在SHT域,采用局部空间频率(space frequency,SF)和局部梯度能量(energy of gradient,EOG)及不同量测(SF,EOG和局部拉普拉斯能量和(sum-modified-Laplacian,SML))激励SCM模型选择纹理信息并构造初始融合图像P。然后,计算图像P与原图像之间差异的显著性特征提取焦距区域。最后,联合聚焦区域产生融合图像。为了验证提出算法的优越性,将文中结果与7种竞争的方法比较,实验结果表明新算法获得了清晰的边缘,产生了良好的视觉感知和较少的失真。
关键词:    图像融合    SHT变换    空间频率    梯度能量    拉普拉斯能量和    焦聚区域检测    差异图像   
Image Fusion Algorithm of Focal Region Detection and TAM-SCM Based on SHT Domain
WANG Feng, CHENG Yongmei, LI Hui
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
Abstract:
The selection of texture information and block ringing effect in multi-focus fusion process, a new multi-focus image fusion algorithm based on Three Activity Measures (TAM) excitation Spiking Cortical Model, (SCM) in shearlet (SHT) domain is proposed. Firstly, in SHT domain, using local spatial frequency (SF), local energy of gradient (EOG) and different measurements (SF, EOG, and local laplace energy sum (SML)) motivated SCM selected the texture information and construct the initial fusion image (P). Then, the focal region was extracted from the significant feature of the difference between the image P and the original image. Finally, the joint focus area produces fusion images. To verify the superiority of the proposed algorithm, compare the results of this paper with seven competing methods. Experimental results show that the algorithm can produce clear edges, good visual perception and less distortion.
Key words:    image fusion    shearlet transform    spatial frequency    gradient energy    Laplacian energy    focus arear detection    difference image   
收稿日期: 2018-03-06     修回日期:
DOI: 10.1051/jnwpu/20193710114
基金项目: 国家自然科学基金(61135001)资助
通讯作者:     Email:
作者简介: 王峰(1981-),西北工业大学博士研究生,主要从事智能信息处理及机器学习研究。
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