Bottle Image De-noising Using Adaptive Threshold Based on Nonsubsampled Contourlet Transform

摘要：

Non-subsampled Contourlet transform(NSCT) with translational invariance was applied to image denoising, which could capture the intrinsic geometrical structure of bottle image. After the scale of NSCT is determined, using NSCT to transform the noisy image of glass bottle. A low frequency component and some high frequency components will be obtained. Through using the coefficients of high frequency components from different directions of the same scale,adaptive thresholds will be got. Combined with hard threshold function, these high frequency components will be treated and new high frequency components will be acquired. Using inverse non-subsampled Contourlet transform to deal with the low frequency component and new high frequency components, a de-noised image of glass bottle is obtained. The experimental results show tbat the method can get higher SNR value of de-noised bottle image and better visual effect compared with other methods.

关键词： Non-subsampled Contourlet transform translational invariance adaptive denoised image

作者: Changhua Lu Jie Shen Xiaoya Yu

作者单位: 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: 1632-1635

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）