摘要
为了解决三维块匹配算法在处理图像边缘上产生的高频伪像和抑制阶梯效应,提出了一种基于广义全变分的自适应BM3D算法。首先,经过预分类得到两个具有不同结构信息的块子集。在具有复杂变化的子集中,考虑到自适应算法可以显著减小BM3D算法用于匹配的遍历范围,对该区域采用自适应参考块匹配;在具有均匀变化的子集中,应用原始大小固定的参考块。针对图像处理产生的阶梯效应,提出一种新型的广义全变分(CTGV),二阶总广义变分能自动平衡图像的一阶和二阶偏导的特性,引入变异系数,可调节广义全变分的扩散效果。通过实验数据对比,该算法相比较于BM3D算法及其他算法,图像的PSNR值提升1~2 dB,SSIM值也有显著提升,同时对比视觉效果,该算法有效地去除了高频伪像和抑制阶梯效应。
In order to solve the three dimensional block matching algorithm on the processing image edge of high-frequency pseudo like ladder and inhibition effect,proposes a adaptive BM3 D algorithm based on generalized variational all.First,after a preliminary classification get two blocks with different structure information subset.In a complex change of subset,considering the adaptive algorithm can significantly reduce the BM3 D algorithm used to match the traversal,to adopt adaptive reference block matching the area,in a uniform variation of subset,application of the original fixed reference block size.The staircase effect in view of the image processing,puts forward a new kind of generalized variational(CTGV),second order total generalized variational can automatic balance of first and second order partial derivative of the image features,introduced the variation coefficient,the adjustable generalized variational diffusion effect.By comparison with the experimental data,the algorithm compared with BM3 D algorithm and other algorithms,image PSNR improvement more than 1~2 dB,SSIM values also have a significant boost,contrast visual effects,this algorithm is effective in addition to the high frequency artifacts and the effect of the inhibition of ladder.
作者
万东东
周先春
昝明远
汪志飞
王新晔
殷豪
Wan Dongdong;Zhou Xianchun;Zan Mingyuan;Wang Zhifei;Wang Xinye;Yin Hao(School of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing 210044,China;School of Artificial Intelligence,Nanjing University of Information Science and Technology,Nanjing 210044,China;Changwang School of Honors,Nanjing University of Information Science and Technology,Nanjing 210044,China)
出处
《电子测量技术》
北大核心
2021年第16期130-134,共5页
Electronic Measurement Technology
基金
国家自然科学基金项目(11202106,61302188)
江苏省“信息与通信工程”优势学科建设项目
江苏高校品牌专业建设工程项目
江苏省大学生创新创业训练计划项目(202010300128P,202110300050Z)资助。
关键词
三维块匹配
变异系数
自适应
广义全变分
3D block matching
coefficient of variation
self adaptation
total generalized variation
