Pavement distress image filtering algo rithm is very important for the pavement distress automatic detection technology . According to the imbalance between signals and noises,this study proposes a nov el 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 denoi sed by the compressed sensing algorithm.In the compressed sensing filtering algorithm,the high-frequency coefficients are ob served by the pseudo-random Fourier matrix and reconstructed by the split Bregman iteration method to get the optimum high-fre quency coefficients.Finally,the optimum high-frequency coefficients and the low-frequency coefficients are reconstruc ted by the inverse NSCT to get the denoised image. The experiment results show that the pavement distress image filtering algorith m in this paper improves the effectiveness of the filtering.