The　conventional　wavelet　denoising　method　based　on　the　simple　threshold　principle　cannot　always　successfully　extract　the　weak　fault　feature　from　the　vibration　signal　with　strong　background　noise,　as　the　noise　of　different　layers　is　individually　estimated.　Inspired　by　the　fact　that　the　wavelet　transform　coefficients　of　adjacent　layers　have　some　similarities　where　the　signal　is　singular,　a　new　method　based　on　dual-tree　complex　wavelet　transform　and　correlation　filter　is　proposed.　The　method　is　an　interactive　process　in　which　its　parameters　are　adaptively　selected　and　the　noise　can　be　efficiently　reduced.　More　important,　the　faint　component　that　is　expected　to　be　extracted　will　be　retained.　The　defect　frequency　can　be　accurately　found　by　the　envelope　demodulation　analysis.　As　an　improvement　to　the　conventional　wavelet　transform　domain　correlation　filter,　it　takes　full　advantage　of　dual-tree　complex　wavelet　transform.　Experimental　and　engineering　application　examples　show　the　method＇s　effectiveness　in　incipient　gearbox　fault　diagnosis.　©　2016,　Editorial　Department　of　JVMD.　All　right　reserved.