In view of the noise problems when detecting the edge of lung images, three points are improved based on the mathematical morphology edge detection. Firstly, connected with three fundamental select principles for the structuring element, i.e. the similarity of shape, the covering of size and the composition of the different structuring elements, it particularly chooses omnidirectional structures and multi-scale structures suitable for the lung images. Secondly, it improves common morphological edge detection operator, and combines omnidirectional structures and multi-scale structures to obtain a new compound morphology edge detection operator which is suitable for edge detection of the lung images. Thirdly, it adds peak signal-to-noise ratio (PSNR) into weight calculation method and improves the method for calculating weights. Finally, it detects the edge of lung noise images with PSNR of 50.684 9 dB through the simulation. Compared with the general algorithm, The results show that the improved algorithm can improve PSNR and mean square error (MSE) substantially and can detect more and better de-noising lung image edge. Applied to other images or different noise images, the proposed algorithm can detect sharper edges of the image, indicating that the algorithm has good robustness.