This　study　examines　the　use　of　UAV　technology　to　capture　images　of　construction　crane　bolts　and　process　them　for　denoising　and　enhancement.　Traditional　image　acquisition　methods　often　struggle　to　capture　clear　bolt　images　due　to　the　variability　of　the　construction　site　environment.　To　address　this　issue,　this　study　employs　UAVs　for　automated　image　acquisition,　resulting　in　significantly　improved　efficiency　and　image　quality.　To　tackle　potential　noise　and　illumination　issues　in　the　resulting　images,　this　paper　presents　a　range　of　image　pre-processing　techniques.　These　include　median　filtering,　mean　filtering,　Gaussian　filtering,　and　efficient　denoising　methods　such　as　the　C-BM3D　algorithm.　Additionally,　histogram　equalization　and　image　enhancement　strategies　based　on　the　Retinex　theory　are　employed　to　further　optimize　image　quality.　The　experimental　results　indicate　that　both　the　C-BM3D　algorithm　and　the　improved　Retinex　algorithm　have　a　significant　effect　on　enhancing　image　clarity.　This　study’s　findings　are　important　not　only　for　improving　the　safety　and　efficiency　of　construction　sites　but　also　for　advancing　image　processing　technology.　©　2024　SPIE.