An　adaptive　filtering　method　for　off-axis　digital　holographic　reconstruction　is　presented.　The　spatial　spectrum　distribution　of　an　off-axis　digital　hologram　is　clustered　based　on　the　K-means　clustering　algorithm　of　unsupervised　machine　learning　.　The　spatial-spectrum　filtering　can　be　carried　out　by　the　quantitative　comparison　of　different　filtering　interception　windows.　The　first-order　spectrum　including　the　object　information　can　be　automatically　located　and　intercepted　after　clustering　the　spatial　spectrum　distribution　of　the　hologram.　The　experiment　results　demonstrate　that　the　reconstruction　images　with　better　resolution　and　imaging　quality　can　be　achieved　by　the　adaptive　filtering　algorithm.　This　adaptive　filtering　reconstruction　based　on　K-means　clustering　provides　a　new　way　of　automatic　reconstruction　imaging　for　off-axis　digital　holography.　©　2022　Optica　Publishing　Group　under　the　terms　of　the　Optica　Open　Access　Publishing　Agreement.