The rapid development of multimedia te chnology has promoted the application and development of image processing and di splay devices.In order to make images optimally displayed on different devices,i t is necessary to adjust the size of the image.Therefore,this paper proposes an image retargeting method based on compressible sensing and seam carving based on deep feature learning.First,extract the feature map of the input image from the pre-trained VGG-19network,calculate the compressibility of the feature image from the deepest layer,and apply the seam carving method on feature fields (FSC ) according to the calculated compressibility to adjust the size of the feature map,and then propagate to the shallow layer in turn to obtain the retargeted ima ge of all the feature layers,and then the pixels at the positions where the inpu t image corresponds to the unstitched portion of the first layer feature image a re removed,and a retargeted image of the original image is obtained.If the size of the target image is not reached,the final scaling is performed.Subjective and objective evaluations were performed on the RetargetMe dataset respectively.The results show that,compared with other methods the retargeting method of this pa per achieves better performance overall.