Denoising of Tube-type Bottle Image Based on Independent Component Analysis and Nonsubsampled Contourlet Transform

摘要：

In this paper a new image denoising algorithm is presented based on independent component analysis (ICA) and nonsubsampled contourlet transform(NSCT), taking full advantage of NSCTs strong points of translationinvariant, multidirection-selectivity and ICAs strong point of higher order statistical property, then a noisy image is denoised by maximum likelihood esrimation of the noisy version of the ICA modeL The simulation results have shown that the performance of the above method is superior both in signal to noise ratio(SNR) and edge preservation. This algorithm is suitable for defects monitoring systems in tube-type bottle.

关键词： Nonsubsampled contourlet transform (NSCT) independent component analysis (ICA) maxrmum likelihood estimalion Image denoising

作者: Xiaoya Yu Changhua Lu Jie Shen

作者单位: School of computer & information Hefei university of technology Hefei Anhui Province, China School of computer & information Hefei university of technology Hefei, Anhui Province, China School of Computer & Information,Hefei University of Technology,Hefei, Anhui Province, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1514-1517

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）