Image　dehazing　is　an　important　research　topic　in　the　field　of　image　processing　and　computer　vision.　Image　dehazing　aims　to　remove　haze　in　images　and　make　image　scenes　clearer.　Image　dehazing　based　on　dark　channel　prior　is　a　currently　popular　type　of　methods.　However,　image　dehazing　results　obtained　by　existing　methods　based　on　dark　channel　prior　usually　have　color　distortion　and　low　brightness　causing　partial　image　details　invisible.　To　alleviate　this　issue,　we　presented　a　modified　method　based　on　dark　channel　prior.　First,　the　proposed　method　estimates　the　value　of　atmospheric　light　by　using　a　quadtree　algorithm,　and　uses　the　dark　channel　prior　to　pixelwisely　estimate　and　optimize　medium　transmission.　Second,　the　proposed　method　uses　a　classic　atmospheric　scattering　model　to　generate　an　initial　image　dehazing　result,　and　transforms　the　result　from　RGB　(Red,　Green,　and　Blue)　color　space　to　HSV　(Hue,　Saturation,　and　Value)　color　space.　Finally,　the　proposed　method　conducts　the　CLAHE　(Contrast　Limited　Adaptive　Histogram　Equalization)　algorithm　on　the　V　component　of　the　initial　result,　and　maps　the　result　into　the　RGB　space　to　obtain　final　image　dehazing　result.　Experimental　results　showed　that　the　proposed　method　effectively　alleviated　color　distortion　and　made　image　scenes　clearer　in　image　dehazing　results.　©　Springer　Nature　Switzerland　AG　2019.