Structure-Preserved NLTV Regularization for Image Denoising

摘要：

Image denoising is an important problem in image processing since noise may interfere with visual or automatic interpretation. This paper proposes a novel Nonlocal Total Variation (NLTV) regularization method to reduce noise in digital images. The data fidelity term in variational framework of NLTV is implemented via iterative nonlocal means, which can preserve the structure information in a denoised image. Experimental results show that our method is very competitive with the NLTV method, especially in preserving image structure and introducing very few artifacts.

关键词： nonlocal regularization image denoising

作者: Hongyi Liu Zhihui Wei

作者单位: School of Science, Nanjing University of Science and Technology, Nanjing, China School of Compute Science and Technology, Nanjing University of Science and Technology, Nanjing, Chi

会议类型: 国际会议

会议名称: 2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

会议地点: 武汉

会议语种:英文

页码: 219-222

在线出版日期: 2011-10-21（万方平台首次上网日期，不代表论文的发表时间）