The　wavelet　de-noising　approach　is　one　of　the　most　efficient　techniques　for　noise　reduction.　Except　for　the　mathematical　elegancy　in　its　theoretical　aspect,　a　successful　application　requires　appropriate　determination　on　the　decomposition　level.　This　paper　proposes　a　novel　approach　to　selecting　an　appropriate　decomposition　level　by　applying　the　Gamma　test　on　the　noisy　data　to　estimate　the　noise　variance.　A　number　of　experiments　were　carried　out　on　a　set　of　smooth　signals　corrupted　by　white　Gaussian　noise　to　verify　the　effectiveness　of　the　proposed　approach　and　a　set　of　traffic　flow　data　was　used　to　demonstrate　the　application　of　the　proposed　approach　on　the　real-world　de-nosing　task.　The　experimental　results　indicate　that　the　proposed　approach　is　effective　to　determine　the　decomposition　level　©　(2013)　Trans　Tech　Publications,　Switzerland.