Considering　the　problems　of　low　grey　contrast,　weak　edges　and　noise　interference　for　the　foam　image　captured　by　the　situation　of　the　poor　light　in　the　floatation　process,　here　is　proposed　a　new　foam　image　multi-scale　enhancement　algorithm　based　on　adaptive　fractional　differential　and　non-subsampled　contourlet　transform　(NSCT).　Firstly,　foam　image　is　decomposed　through　NSCT,　the　low　frequency　sub-band　image　is　enhanced　by　combining　the　adaptive　fractional　differential　order　function　constructed　on　the　basis　of　pixel　gradient　feature,　with　the　Tiansi　ope-rator　which　is　improved　by　a　set　of　brightness　control　parameters.　Secondly,　for　high　frequency　sub-bands,　thre-shold　is　adaptively　computed　according　to　the　energy　distribution,　which　is　proposed　to　eliminate　noise　with　the　scale　correlation　coefficient,　and　the　edge　coefficients　are　enhanced　by　a　nonlinear　enhancement　function.　Finally,　the　processed　image　is　reconstructed　through　NSCT.　Enhancement　experiment　is　performed　by　different　kinds　of　bubble　size　images.　Experimental　results　show　that,　compared　to　other　current　algorithms,　the　proposed　algorithm　is　superior　in　improving　the　lightness,　contrast,　definition　and　comentropy　of　the　foam　image,　and　is　successful　in　maintaining　more　texture　details,　which　can　also　achieve　much　better　performance　to　enhance　bubble　edges　while　removing　the　image　noise.　It　lays　a　foundation　for　the　subsequent　foam　image　segmentation　and　edge　detection.　©　2018,　Editorial　Department,　Journal　of　South　China　University　of　Technology.　All　right　reserved.