Aiming at the problem of background information blur and loss caused by rain streaks in machine vision scene images, a method of image de-raining based on octave convolution and attention mechanism is proposed. Firstly, a de-raining model based on spatial-frequency domain is established, and a frequency feature decomposition module is designed based on spatial scale transformation and octave convolution. The mapping relationship between frequency features and rain streaks features is obtained through learning, so as to reduce spatial redundancy of low-frequency features and improve network operation efficiency. Secondly, the multi-layer channel attention module is designed to map the weight information of rain streaks, enhance important features, mine the brightness difference between rain streaks layers, and improve the performance of rain streaks detection. Finally, the rain streaks information of different components is decomposed iteratively through sequence operation, and then the de-raining of scene image is completed. Experimental results show that the proposed method has good removal performance for rain streaks and raindrops with different directions and shapes, and also has good protection for details and edge information of background image.