Learning based intelligent image retargeting technique

Abstract

There has been a wide range of image retargeting( IR) approaches,in order to solve the problem of adapting images to different display resolutions. A fast image retargeting method was proposed,which was based on image columns. Firstly,the method would calculate a saliency map of the original image. Secondly,a group of scaling factors were generated for image pixel fusion,which was used to get the result image of the target image size. Each image column corresponded to its scaling factor. For different images,an adaptive upper bound was obtained by machine learning,for scaling factor assignment. This upper bound was set to limit the column width and can reduce image distortion. The experiment results prove that this adaptive upper bound results in a better performance. Moreover,this method has a low complexity,thus it calculates fast,as it is based on image columns instead of pixels.