Images/videos　captured　in　low-light　conditions　often　present　low　luminance　and　contrast.　Although　the　existing　low-light　enhancement　algorithms　can　improve　the　subjective　perception,　color　distortion　and　over-enhancement　are　extremely　obvious,　which　will　disturb　the　subsequent　intelligent　analysis.　Therefore,　a　naturalness-preserved　low-light　enhancement　algorithm　for　intelligent　analysis　is　proposed　in　this　paper.　An　enhancement　model　is　established　in　RGB　color　space.　Images　of　ColorChecker　color　chart　are　captured　under　a　series　of　light　conditions.　To　preserve　the　naturalness,　the　factors　of　the　proposed　enhancement　model　are　estimated　by　the　images　captured　in　practical　illumination　environment.　Experimental　results　demonstrate　that　the　proposed　algorithm　can　produce　natural　enhanced　results　and　improve　the　performance　of　vehicle　license　plate　localization　and　skin　color　detection　compared　to　the　existing　algorithms.　Furthermore,　the　proposed　algorithm　can　process　the　720p　videos　at　the　speed　of　28.3　fps　on　average.