With　the　development　of　remote　sensing　satellites,　radar　imaging,　and　unmanned　aircraft,　how　to　utilize　the　modern　image　processing　technology　to　extract　road　network　has　been　a　hot　research　topic　of　remote　sensing　and　geographic　information　technology.　Therefore,　a　visual　saliency　based　automatic　road　extraction　method　from　high-resolution　multispectral　satellite　images　is　proposed　in　this　paper.　Firstly,　the　color,　intensity　and　orientation　features　are　extracted　to　construct　visual　attention　model　for　road　saliency　region　detection.　Then　road　network　is　extracted　by　adaptive　region　growing　algorithm　after　automatically　setting　the　pixels　with　larger　saliency　as　seed　points.　At　last,　the　non-road　parts　and　noises　are　removed　from　road　network　by　using　morphological　operations.　The　experimental　results　show　that　the　proposed　automatic　road　extraction　method　can　achieve　a　superior　performance　in　completeness　and　correctness　than　other　traditional　methods.　©　2015　ACM.