Texture Preserving Perona-Malik Model

摘要：

The Perona-Malik (PM) model, an effective anisotropic diffusion, can preserve edges while removing the noise. However, the disadvantage of the PM model is tending to impair textures and details so that denoising is not sufficient in the whole process. For this reason, we present a novel texture preserving Perona-Malik (TPPM) models based on the local directional variance. In the TPPM model, the diffusion coefficient of the PM model is adaptively determined to be low diffusion in large variance domain and be high diffusion in low variance domain. The related parameters are studied. Comparative results on real image denoising demonstrate that our model outforms the PM model, classical total variational (TV) method, a wavelet-based method and a nonlocal means filter in signal-to-noise ratio. The proposed model is also competitive with other methods visually. Furthermore, the execution times are very fast.

关键词： texture preserving image denoising anisotropic diffusion Wiener filter

作者: Xiaobo Zhang Xiaobo Zhang Xiangchu Feng

作者单位: School of Mathematics and Information Science Xianyang Normal University Xianyang, China Department of Mathematics Xidian University Xian. China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 827-830

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）