Background Modeling in Compressed Sensing Scheme

摘要：

A background modeling scheme in compressed sensing (CS) imaging system is proposed in this paper, in which background evaluation is performed on the measurement vectors directly before reconstruction. The estimated background measurement vector is constructed through average, running average, median and block-based selective method respectively. Then the estimated background image is reconstructed using the background model measurements through the gradient projection for sparse reconstruction (GPSR) algorithm. The simulations show that the proposed background modeling algorithms in CS scheme provide promising results.

关键词： background modeling compressed sensing average running average median block

作者: Xue Wang Fengxia Liu Zhongfii Ye

作者单位: Institute of Statistical Signal Processing University of Science and Technology of China Hefei, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Industrial Electronics(2011年信息与工业电子国际会议 ICIIE 2011)

会议地点: 成都

会议语种:英文

页码: 442-446

在线出版日期: 2011-01-14（万方平台首次上网日期，不代表论文的发表时间）