The　images　in　the　low-light　and　narrow　environment　generally　have　the　problems　of　non-uniform　illumination,　low　contrast,　and　large　random　noise.　Existing　algorithms　are　mostly　subject　to　the　imaging　effect　of　the　original　image,　and　are　prone　to　failure　in　extremely　weak　light　or　strong　reflective　environments.　This　paper　proposes　an　active　and　adaptive　image　enhancement　method.　First　of　all,　this　paper　combines　the　distributed　light　source　model　and　the　difference　in　brightness　between　frames　to　complete　active　feedback　fill　light,　which　improves　the　quality　of　the　input　image.　Then　gamma　correction,　contrast　limited　adaptive　histogram　equalization　and　bilateral　filter　are　designed　to　enhance　image　details　and　suppress　noise　amplification.　Combined　with　fuzzy　inference　parameter　self-adjustment　method,　algorithm　adaptability　is　improved.　Finally,　through　experimental　verification,　the　method　proposed　in　this　paper　can　effectively　enhance　the　images　in　the　low-light　and　narrow　environment.