To　assist　underwater　object　detection　for　better　performance,　image　enhancement　technology　is　often　used　as　a　pre-processing　step.　However,　most　of　the　existing　enhancement　methods　tend　to　pursue　the　visual　quality　of　an　image,　instead　of　providing　effective　help　for　detection　tasks.　In　fact,　image　enhancement　algorithms　should　be　optimized　with　the　goal　of　utility　improvement.　In　this　paper,　to　adapt　to　the　underwater　detection　tasks,　we　proposed　a　lightweight　dynamic　enhancement　algorithm　using　a　contribution　dictionary　to　guide　low-level　corrections.　Dynamic　solutions　are　designed　to　capture　differences　in　detection　preferences.　In　addition,　it　can　also　balance　the　inconsistency　between　the　contribution　of　correction　operations　and　their　time　complexity.　Experimental　results　in　real　underwater　object　detection　tasks　show　the　superiority　of　our　proposed　method　in　both　generalization　and　real-time　performance.　©　2023,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd.