Pavement Image Denoising Based on Shearlet Treansform
A novel pavement image denoising method based on shearlet transform is proposed in this paper. Because that the pavement crack has continuous liner geometrical feature which can be captured by shearlets very efficiently with more directions than wavelets, the pavement image denoising method based on the shearlet transform can obtain a great inprovement than traditional method. Background fitting is used to deal with the low frequency component of the image, which can banlance the energy distribution of the pavement image. Then coarse scale coefficients of shearlet are selected under multiple thresholds. The coefficients obtained by low threshold is used for reconstruction of the main parts of cracks, and the coefficients obtained by high threshold is employed to extract crack position and direction information, which is fused with the threshold at fine scale to distinguish the noise and fine parts of cracks. The experimental results show that this method can smooth the most of noisy spots but keep the cracks details well and have less pseudo-Gibbs artifacts.
pavement image denoising shearlet transform background fitting directional information
Chengdong Wu Baihua Lu Dongyue Chen Li Wang
School of Information Science & Engineering Northeastern University Shenvana. China
国际会议
2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)
大连
英文
721-724
2011-07-29（万方平台首次上网日期，不代表论文的发表时间）