Recent　years　have　witnessed　the　widespread　applications　of　mobiles　and　other　portable　electronic　devices,　involving　a　variety　of　screen　content　photos.　Different　from　natural　scene　photos,　screen　content　photos　are　composed　of　more　lines,　fewer　colors　and　unique　text　messages.　Thus,　it　is　difficult　to　realize　the　satisfactory　enhancement　effect　of　screen　content　photos　using　traditional　image　enhancement　technology　since　they　are　designed　for　the　natural　scene.　In　this　paper,　we　develop　a　novel　enhancement　model　for　screen　content　photos　by　considering　text　and　picture　separately.　To　be　specific,　we　first　use　a　fully　convolutional　network　to　divide　a　screen　content　photo　into　three　independent　parts:　picture　region,　foreground　text　region,　and　background.　Second,　an　optimal　modification　of　histogram　is　used　to　automatically　enhance　the　picture　region’s　contrast,　and　the　guided　image　filter　is　used　to　enhance　the　foreground　text　region.　Third,　the　enhanced　picture　region,　the　enhanced　foreground　text　region,　and　background　are　fused　to　obtain　the　final　enhanced　image.　Experimental　results　show　that　our　model　has　produced　less　noise　and　derived　outstanding　enhancement　effect　than　the　popular　enhancement　techniques.　©　2021,　Springer　Nature　Singapore　Pte　Ltd.