A compressed sensing pavement distress image filtering algorithm based on NSCT domain

作者：Shen Yu^*; Dang Jian Wu; Wang Yang Ping; Feng Xin

来源：Journal of Optoelectronics - Laser, 2014, 25(8): 1620-1626.

• Automatic Detection
• Compressive sensing
• Filtering algorithm
• High frequency HF
• Image filtering algorithms
• Non subsampled contourlet transform (NSCT)
• Pavement distress
• Split bregman iterations

Pavement distress image filtering algorithm is very important for the pavement distress automatic detection technology. According to the imbalance between signals and noises, this study proposes a novel compressed sensing filtering algorithm in nonsubsampled contourlet transform (NSCT) domain. Firstly the NSCT is adopted to conduct the multi-scale and multi-direction decomposition on the noisy pavement distress image. The decomposition results can give the low-frequency coefficients and the high-frequency coefficients. Secondly, the high-frequency coefficients are denoised by the compressed sensing algorithm. In the compressed sensing filtering algorithm, the high-frequency coefficients are observed by the pseudo-random Fourier matrix and reconstructed by the split Bregman iteration method to get the optimum high-frequency coefficients. Finally, the optimum high-frequency coefficients and the low-frequency coefficients are reconstructed by the inverse NSCT to get the denoised image. The experiment results show that the pavement distress image filtering algorithm in this paper improves the effectiveness of the filtering.

• 出版日期2014