Super　resolution　image　restoration　technology　is　a　hot　field　of　image　processing　in　the　field　of　video　surveillance,　image　processing,　forensic　analysis,　with　a　wide　range　of　application　requirements.　In　recent　years,　the　rapid　development　of　deep　learning　in　the　field　of　multimedia　processing,　deep　learning　based　super-resolution　images　restoration　has　gradually　become　a　mainstream　technology.　This　paper　reviews　the　existing　deep　learning　based　image　super-resolution　restoration　work.　In　terms　of　network　type,　network　structure,　and　training　methods,　the　advantages　and　disadvantages　of　the　prior　art　are　analyzed　and　the　development　contexts　are　sorted　out.　On　this　basis,　the　paper　further　points　out　the　future　direction　of　the　restoration　technique　based　on　deep　learning　of　the　super-resolution　image.　Copyright　©　2017　Acta　Automatica　Sinica.　All　rights　reserved.