Autofocusing　is　the　key　of　numerical　reconstruction　in　digital　holographic　microscopy.　Based　on　Fresnel　transform　algorithm,　the　performance　of　six　typical　autofocusing　evaluation　functions　are　studied　experimentally.　A　method　which　only　uses　part　of　the　reconstruted　image　as　autofocusing　area　is　proposed　to　decrease　the　calculating　time.　The　results　show　that　these　functions　have　better　unimodality,　same　adjusting　focus　range　and　accuracy,　but　the　functions　related　with　gradient　are　too　slow　to　use　in　the　numerical　quasi-real　time　reconstruction.　Fourier　spectrum　function　is　the　optimum　one　for　its　minimum　calculating　time.　The　adjusting　focus　time　can　be　decreased　greatly　by　choosing　a　part　of　the　reconstructed　image　as　calculating　area.　For　low　signal-to-noise　ratio　hologram,　the　autofocusing　accuracy　and　image　quality　can　be　improved　by　applying　Wiener　self-adaptive　filter.