Ocular　artifact　(OA)　is　one　of　the　main　interferences　in　electroencephalogram　(EEG)　recordings.　It　appears　as　a　big　pulse　and　has　a　strong　impact　to　EEG　signals.　To　overcome　OA　interference　in　EEG　data,　a　novel　automatic　method　of　OA　removal,　denoted　as　DWICA,　was　proposed　in　this　paper.　In　DWICA,　the　discrete　wavelet　transform　(DWT)　is　applied　to　every　recorded　signal　to　obtain　multiple　scale　coefficients.　Then　the　independent　component　analysis　(ICA)　algorithm　is　used,　and　its　input　is　the　coefficients　connected　in　series.　Thus　the　independent　components　are　acquired　quickly　in　wavelet　domain.　The　criterion　of　angle　cosine　is　introduced　to　recognize　ocular　artifact,　and　the　corresponding　component　is　set　to　zero.　Furthermore,　the　artifact　free　components　are　projected　to　original　electrodes　with　inverse　ICA　algorithm.　Finally,　DWT　is　inversed　to　obtain　the　artifact　free　brain　signals.　Quantitative　studies　about　suppression　of　OA　distorting　the　underlying　cerebral　activity　and　accurate　evaluation　on　denoising　effect　of　DWICA　are　finished　in　this　paper.　Experiment　results　show　that　DWICA　is　preferable　and　effective　in　automatic　OA　correction.　Meanwhile,　DWICA　is　powerful　in　noise　immunity　and　fast　in　convergence　rate,　and　it　provides　a　preferable　method　for　EEG　preprocessing　on-line.