A Sparse Point Representation(SPR) based on interpolation wavelets is presented. The SPR is implemented for the purpose of CFD data compression. Unlike conventional wavelet transformation, the SPR relieves computing workload in the similar fashion of lifting scheme that includes splitting and prediction procedures in sequence. However, SPR skips update procedure that is major part of lifting scheme. Data compression can be achieved by proper thresholding method. The advantage of the SPR method is that, by keeping even point physical values, low frequency filtering procedure is omitted and its related unphysical thresholing mechanism can be avoided in reconstruction process. Extra singular feature detection algorithm is implemented for preserving singular features such as shock and vortices. Several numerical tests show the adequacy of SPR for the CFD data. It is also shown that it can be easily extended to nonlinear adaptive wavelets for enhanced feature capturing.