The　subjective　visual　experience　of　viewing　images　using　a　variety　of　display　devices　is　usually　affected　by　image　retargeting　operation.　To　improve　the　consistency　between　subjective　perception　and　objective　assessment　for　the　retargeted　images,　we　present　an　objective　retargeted　image　quality　assessment　(RIQA)　method　based　on　multi-scale　distortion-aware　(MSDA)　features.　Because　semantic　distortion　and　detail　distortion　appear　on　different　scales　of　the　image,　we　propose　to　extract　distortion-aware　features　from　multiple　scales　of　the　image.　Specifically,　we　present　an　accurate　measurement　for　the　aspect　ratio　similarity　(ARS)　between　the　original　and　retargeted　images.　Furthermore,　we　use　a　fused　visual　attention　map　to　simulate　the　subjective　attention　of　the　human　visual　system　to　the　image.　The　experimental　results　on　the　two　benchmark　databases　show　that　the　Kendall　rank　correlation　coefficient　(KRCC),　Pearson　linear　correlation　coefficient　(PLCC),　and　Spearman　rank-order　correlation　coefficient　(SRCC)　indicators　of　the　proposed　MSDA　method　are　4.1%,　1.8%,　and　4.5%　higher　than　the　optimal　method　in　the　comparative　methods,　respectively.　©　2019,　Editorial　Board　of　JBUAA.　All　right　reserved.