In　essence,　image　super-resolution　refers　to　the　transformation　from　small　size　image　to　large　size　image,　that　is,　the　increase　of　pixel　density　of　image　can　provide　more　detailed　information.　It＇s　well-known　that　1D　super-resolution　model　can　not　be　written　directly　into　the　form　of　2D　model,　because　the　matrix　dimension　of　high-solution　image　and　low-solution　image　does　not　agree.　The　proposed　2D-based　blind　super-resolution　algorithm　combining　with　sparse　representation　model　and　TV　term.　The　proposed　method　is　to　reduce　the　complexity　of　the　operation　by　decomposing　the　blur　matrix　and　the　sampling　matrix　in　the　horizontal　(row)　and　vertical　(column)　directions.　The　experimental　results　show　that　the　proposed　method　can　better　protect　the　edge　and　provide　more　texture　structure.　©　2019　IEEE.