The　wavelet　estimations　have　made　great　progress　when　an　unknown　density　function　belongs　to　a　certain　Besov　space.　However,　in　many　practical　applications,　one　does　not　know　whether　the　density　function　is　smooth　or　not.　It　makes　sense　to　consider　the　mean　L-p-consistency　of　the　wavelet　estimators　for　f　is　an　element　of　L-p　(1　＜=　p　＜=　infinity).　In　this　paper,　the　authors　will　construct　wavelet　estimators　and　analyze　their　L-p(R)　performance.　They　prove　that,　under　mild　conditions　on　the　family　of　wavelets,　the　estimators　are　shown　to　be　L-p　(1　＜=　p　＜=　infinity)-consistent　for　both　noiseless　and　additive　noise　models.