Rendering　spatial　sound　scenes　via　audio　objects　has　become　popular　in　recent　years,　since　it　can　provide　more　flexibility　for　different　auditory　scenarios,　such　as　3D　movies,　spatial　audio　communication　and　virtual　classrooms.　To　facilitate　high-quality　bitrate-efficient　distribution　for　spatial　audio　objects,　an　encoding　scheme　based　on　intra-object　sparsity　(approximate　k-sparsity　of　the　audio　object　itself)　is　proposed　in　this　paper.　The　statistical　analysis　is　presented　to　validate　the　notion　that　the　audio　object　has　a　stronger　sparseness　in　the　Modified　Discrete　Cosine　Transform　(MDCT)　domain　than　in　the　Short　Time　Fourier　Transform　(STFT)　domain.　By　exploiting　intra-object　sparsity　in　the　MDCT　domain,　multiple　simultaneously　occurring　audio　objects　are　compressed　into　a　mono　downmix　signal　with　side　information.　To　ensure　a　balanced　perception　quality　of　audio　objects,　a　Psychoacoustic-based　time-frequency　instants　sorting　algorithm　and　an　energy　equalized　Number　of　Preserved　Time-Frequency　Bins　(NPTF)　allocation　strategy　are　proposed,　which　are　employed　in　the　underlying　compression　framework.　The　downmix　signal　can　be　further　encoded　via　Scalar　Quantized　Vector　Huffman　Coding　(SQVH)　technique　at　a　desirable　bitrate,　and　the　side　information　is　transmitted　in　a　lossless　manner.　Both　objective　and　subjective　evaluations　show　that　the　proposed　encoding　scheme　outperforms　the　Sparsity　Analysis　(SPA)　approach　and　Spatial　Audio　Object　Coding　(SAOC)　in　cases　where　eight　objects　were　jointly　encoded.