摘要
进行参考图像与目标图像的匹配是数字散斑图像相关分析中很关键的一个环节,完成这一任务的主流方法是使用传统的互相关工具来评估局部图像原始像素数据之间的相关度,以得到的结果来确定匹配的位置。鉴于相关滤波器在计算机视觉的目标跟踪领域有良好的性能表现,而核函数又可以作为获取图像数据更深层次特征的桥梁,核相关滤波算法被作为一种新的相关度评估工具被应用于数字散斑图像的相关分析。在一定椒盐噪声和尺寸压缩的条件下,实验数据表明,这一方案具有准确性高和性能稳定的特点。
For digital speckle image correlation analysis,it is one of the critical steps to find out the match point between the reference image and tar⁃get image.The common approach for this task is that making use of the traditional cross-correlation as a tool to estimate the correlation of raw data between sub-windows from reference image and target image.And the match point is located depending on the correlation value.Correlation filter has been proved as an effective solution for object tracking in computer vision,and kernel trick bridges the gap between raw data and its high-dimensional features.Kernel correlation filter may be a better method for speckle image correlation analysis.Experi⁃mental result shows that kernel correlation filter has advantage of accuracy and robust under a range of impulse noise and scaling which is close to realistic situation.
作者
马如豹
申小敏
李翔
熊建斌
MA Ru-bao;SHEN Xiao-min;LI Xiang;XIONG Jian-bin(Department of Electronic Information and Electrical Engineering,Xiangnan University,Chenzhou 423000;Department of Automation,Guangdong Polytechnic Normal University,Guangzhou 510000)
出处
《现代计算机》
2020年第35期70-74,90,共6页
Modern Computer
基金
国家自然科学基金青年项目(No.71802055)
湖南省自然科学基金面上项目(No.2020JJ4565)。
关键词
核方法
相关滤波
数字图像相关
散斑图像
Kernel Trick
Correlation Filter
Digital Image Correlation
Speckle Image