This　study　proposed　a　simple　Smoother　without　any　local　adjustments　based　on　Continuous　Wavelet　Transform　(SCWT).　And　then　it　evaluated　its　performance　together　with　other　commonly　applied　techniques　in　phenological　estimation.　These　noise　reduction　methods　included　Savitzky-Golay　filter　(SG),　Double　Logistic　function　(DL),　Asymmetric　Gaussian　function　(AG),　Whittaker　Smoother　(WS)　and　Harmonic　Analysis　of　Time-Series　(HANTS).　They　were　evaluated　based　on　fidelity　and　smoothness,　and　their　efficiencies　in　deriving　phenological　parameters　through　the　inflexion　point-based　method　with　the　8　day　composite　Moderate　Resolution　Imaging　Spectroradiometer　(MODIS)　2-band　Enhanced　Vegetation　Index　(EVI2)　in　2013　in　China.　The　following　conclusions　were　drawn:　(1)　The　SG　method　exhibited　strong　fidelity,　but　weak　smoothness　and　spatial　continuity.　(2)　The　HANTS　method　had　very　robust　smoothness　but　weak　fidelity.　(3)　The　AG　and　DL　methods　performed　weakly　for　vegetation　with　more　than　one　growth　cycle　(i.e.,　multiple　crops).　(4)　The　WS　and　SCWT　smoothers　outperformed　others　with　combined　considerations　of　fidelity　and　smoothness,　and　consistent　phenological　patterns　(correlation　coefficients　greater　than　0.8　except　evergreen　broadleaf　forests　(0.68)).　(5)　Compared　with　WS　methods,　the　SCWT　smoother　was　capable　in　preservation　of　real　local　minima　and　maxima　with　fewer　inflexions.　(6)　Large　discrepancy　was　examined　from　the　estimated　phenological　dates　with　SG　and　HANTS　methods,　particularly　in　evergreen　forests　and　multiple　cropping　regions　(the　absolute　mean　deviation　rates　were　6.2-17.5　days　and　correlation　coefficients　less　than　0.34　for　estimated　start　dates).　(C)　2015　Elsevier　B.V.　All　rights　reserved.