Electroencephalography　(EEG)　is　easily　affected　by　ocular　artifact　(OA),　which　appears　in　EEG　randomly　as　a　big　pulse.　Based　on　discrete　wavelet　transform　(DWT)　and　independent　component　analysis　(ICA),　a　novel　automatic　method　of　OA　removal,　denoted　as　DWICA,　was　proposed.　Firstly,　DWT　was　applied　to　the　recorded　EEG　and　electrooculogram　(EOG)　to　obtain　multiple　scale　coefficients,　and　the　combined　coefficients　were　considered　as　the　input　for　ICA.　Secondly,　the　independent　components　were　acquired　based　on　FastICA　algorithm　with　negentropy　criterion.　The　angle　cosine　criterion　was　introduced　to　recognize　ocular　artifact　component.　Furthermore,　the　inverse　algorithm　of　ICA　was　applied　to　project　the　independent　components　without　OA　to　original　electrodes.　Finally,　the　EEG　were　reconstructed　using　the　inverse　algorithm　of　DWT,　and　then　the　pure　EEG　were　obtained.　Experimental　results　show　that　DWICA　is　preferable　in　automatic　removal　of　OA.　The　method　provides　a　new　idea　for　on-line　preprocessing　of　EEG　signals.