首先，对于四叉树的分割形式，大家想必都已经了解了，这里就不进行过多的赘述，下面是常见的四叉树结构示意图：

接下来是代码部分：

该过程主要由TEncCu::xCompressCU函数的递归实现。

    // further split进一步进行CU的分割
    if( bSubBranch && bTrySplitDQP && uiDepth < g_uiMaxCUDepth - g_uiAddCUDepth )
    {
      UChar       uhNextDepth         = uiDepth+1;
      TComDataCU* pcSubBestPartCU     = m_ppcBestCU[uhNextDepth];
      TComDataCU* pcSubTempPartCU     = m_ppcTempCU[uhNextDepth];

      for ( UInt uiPartUnitIdx = 0; uiPartUnitIdx < 4; uiPartUnitIdx++ )//每次分成四个更小的CU     {         pcSubBestPartCU->initSubCU( rpcTempCU, uiPartUnitIdx, uhNextDepth, iQP );           // clear sub partition datas or init.
        pcSubTempPartCU->initSubCU( rpcTempCU, uiPartUnitIdx, uhNextDepth, iQP );           // clear sub partition datas or init.

        Bool bInSlice = pcSubBestPartCU->getSCUAddr()+pcSubBestPartCU->getTotalNumPart()>pcSlice->getDependentSliceCurStartCUAddr()&&pcSubBestPartCU->getSCUAddr()getDependentSliceCurEndCUAddr();
        if(bInSlice && ( pcSubBestPartCU->getCUPelX() < pcSlice->getSPS()->getPicWidthInLumaSamples() ) && ( pcSubBestPartCU->getCUPelY() < pcSlice->getSPS()->getPicHeightInLumaSamples() ) )
        {
          if( m_bUseSBACRD )
          {
            if ( 0 == uiPartUnitIdx) //initialize RD with previous depth buffer
            {
              m_pppcRDSbacCoder[uhNextDepth][CI_CURR_BEST]->load(m_pppcRDSbacCoder[uiDepth][CI_CURR_BEST]);
            }
            else
            {
              m_pppcRDSbacCoder[uhNextDepth][CI_CURR_BEST]->load(m_pppcRDSbacCoder[uhNextDepth][CI_NEXT_BEST]);
            }
          }

#if AMP_ENC_SPEEDUP
          if ( rpcBestCU->isIntra(0) )
          {
            xCompressCU( pcSubBestPartCU, pcSubTempPartCU, uhNextDepth, SIZE_NONE );//递归函数
          }
          else
          {
            xCompressCU( pcSubBestPartCU, pcSubTempPartCU, uhNextDepth, rpcBestCU->getPartitionSize(0) );//递归函数
          }
#else
          xCompressCU( pcSubBestPartCU, pcSubTempPartCU, uhNextDepth );         
#endif

          rpcTempCU->copyPartFrom( pcSubBestPartCU, uiPartUnitIdx, uhNextDepth );         // Keep best part data to current temporary data.
          xCopyYuv2Tmp( pcSubBestPartCU->getTotalNumPart()*uiPartUnitIdx, uhNextDepth );
        }
        else if (bInSlice)
        {
          pcSubBestPartCU->copyToPic( uhNextDepth );
          rpcTempCU->copyPartFrom( pcSubBestPartCU, uiPartUnitIdx, uhNextDepth );
        }
      }

既然已经知道，CU的分割是通过递归实现的，那么怎么确定哪个uiDepth的CU为rpcBestCU呢？
上述递归函数结束后，然后再通过xCheckBestMode( rpcBestCU, rpcTempCU, uiDepth);判断决定是否选择本层CU还是下层CU.

以下是编程实现输出一个LCU的分割模式：

  // We need to split, so don't try these modes.
  if(!bSliceEnd && !bSliceStart && bInsidePicture )
  {
    for (Int iQP=iMinQP; iQP<=iMaxQP; iQP++)     {       if (isAddLowestQP && (iQP == iMinQP))       {         iQP = lowestQP;       }       // variables for fast encoder decision       bEarlySkip  = false;       bTrySplit    = true;       fRD_Skip    = MAX_DOUBLE;       rpcTempCU->initEstData( uiDepth, iQP );
     //==输出分区深度信息depth==//
      cout<<"Depth:";
      for(Int i=0;i<=uiDepth;i++)
       cout<<"->";
       cout<<uiDepth<<endl;

      // do inter modes, SKIP and 2Nx2N

打印输出的结构为：
 

Depth:->0
Depth:->->1
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->1
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->1
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->1
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->2
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3
Depth:->->->->3