A Novel Hybrid Compressed Sensing Image Reconstrcution Method

摘要：

In this paper, a hybrid approach of image reconstruction from highly incomplete data is introduced. The method is a weighted recursive filtering procedure. At each iteration, random noise is first injected in the unknown portion of the spectrum, and then a reweighted denoising filter consisting of Block Matching 3D (BM3D) filter and multiscalc L0 -continuation filter is exploited to attenuate the noise in the image domain and reveal new features and details, finally those new features are projected onto the unknown portion of the spectrum to update the K-space data. The proposed method avoids local solutions and recovers the features and details of the image efficiently by utilizing advantages of both filters. The experimental results on both simulated and real images consistently demonstrate that the proposed approach can efficiently reconstruct the image with high image quality.

关键词： spatially adaptive image denoising filter BM3D bilateral filtering compressed sensing

作者: Shanshan Wang Qiegen Liu Jianhua Luo Yuemin Zhu

作者单位: College of Life Science and Technology Shanghai Jiaotong University Shanghai, China College of Life Science and Technology hanghai Jiaotong University Shanghai, China CREATIS CNRS UMR 5220 Inserm U630 INSA Lyon University of Lyon Villeurbanne, FranceIn this paper, a

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 56-60

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）