Images　of　roads　captured　by　visual　surveillance　system　are　usually　degraded　by　scattering　due　to　atmospheric　particles　such　as　haze,　fog　and　mist,　which　could　frequently　bring　great　difficulties　to　the　transportation.　In　this　paper,　a　novel　method　was　proposed　based　on　weighted　least　squares　(WLS)　to　remove　fog　from　a　single　input　image.　The　proposed　algorithm　begins　with　estimation　of　atmospheric　light　and　white　balance.　Then,　through　the　constraint　from　the　road　environment,　the　weighted　least　squares　(WLS)　framework　was　constructed　to　estimate　atmospheric　veil,　and　restore　the　fog　image　by　inverting　the　atmospheric　scattering　model.　The　experimental　results　demonstrates　that,　compared　with　the　existing　algorithm,　the　proposed　method　can　remove　the　fog　effectively,　eliminate　the　Halo　effects,　obtain　good　restoration　of　distant　scene　details,　and　thus　realize　the　improvement　of　traffic　image　visibility.　©,　2015,　Chinese　Society　of　Astronautics.　All　right　reserved.