摘要
图像去模糊是图像处理的一个重要领域,采用重叠组稀疏总变差函数(OGSTV)不仅保留了图片的边缘特性,而且能够抑制阶梯效应,被广泛应用于图像去模糊技术。重叠组稀疏总变差函数通常利用交替方向乘子(ADMM)进行模型求解,其惩罚因子是一个不易调节的关键因素。为此,本文通过自适应地调整惩罚因子,能够兼顾计算速度和算法鲁棒性,复原出质量较佳的图片。实验结果表明,这一方法在相对误差(RE)、峰值信噪比(PSNR)和信噪比(SNR)等方面优于其他模型。
Image deblurring is an important field of image processing.The overlapped group sparse total variation function(OGSTV)not only preserves the edge characteristics of images,but also inhibits the step effect,which is widely applied in image deblurring technology.The sparse total variation function of overlapping group usually uses the alternating direction multiplier(ADMM)to solve the model,and the penalty factor is a key factor which is not easy to adjust.For this reason,this paper adaptively adjusts the penalty factor,which can give consideration to the speed of calculation and the robustness of the algorithm,and restore the better quality pictures.The experimental results show that the method is superior to other models in relative error(RE),peak signal to noise ratio(PSNR)and signal to noise ratio(SNR).
作者
陈小莉
CHEN Xiao-li(College of Electronics and Information Engineering,Ankang University,Ankang 725000,China)
出处
《电子设计工程》
2019年第5期189-193,共5页
Electronic Design Engineering
关键词
图像去模糊
重叠组稀疏
总变差函数
交替乘子
image deblurring
overlapping group sparsity
total variation function
alternating direction multiplier
