H.265之三 -帧内预测（3）

今天主要介绍帧内预测一个很重要的函数initAdiPattern，它的主要功能有三个，（1）检测当前PU的相邻样点包括左上、上、右上、左、左下邻域样点值的可用性，或者说检查这些点是否存在；（2）参考样点的替换过程，主要实现的是JCTVC-J1003即draft 8.4.4.2.2的内容，主要由函数fillReferenceSamples来完成，这个在之前的文章已经讨论过了；（3）相邻样点即参考样点的平滑滤波，主要实现draft 8.4.4.2.3的内容。话不多说，下面给出initAdiPattern的实现和我个人的一些注释，供大家参考。

Void TComPattern::initAdiPattern( TComDataCU* pcCU, UInt uiZorderIdxInPart, UInt uiPartDepth, Int* piAdiBuf, Int iOrgBufStride, Int iOrgBufHeight, Bool& bAbove, Bool& bLeft, Bool bLMmode ){//! bLMmode is usually false   Pel*  piRoiOrigin;  Int*  piAdiTemp;  UInt  uiCuWidth   = pcCU->getWidth(0) >> uiPartDepth; //!< CU的宽度  UInt  uiCuHeight  = pcCU->getHeight(0)>> uiPartDepth; //!< CU的高度  UInt  uiCuWidth2  = uiCuWidth<<1;  UInt  uiCuHeight2 = uiCuHeight<<1;  UInt  uiWidth;  UInt  uiHeight;  Int   iPicStride = pcCU->getPic()->getStride();  Int   iUnitSize = 0;  Int   iNumUnitsInCu = 0;  Int   iTotalUnits = 0;  Bool  bNeighborFlags[4 * MAX_NUM_SPU_W + 1];  //!< 用于存放4个方向上的相邻样点值的可用性, 4 x 32 + 1  Int   iNumIntraNeighbor = 0; //!< 给可用邻块进行计数    UInt uiPartIdxLT, uiPartIdxRT, uiPartIdxLB;  //! 获取当前PU左上角LT，右上角RT以及左下角LB 以4x4块为单位的Zorder  pcCU->deriveLeftRightTopIdxAdi( uiPartIdxLT, uiPartIdxRT, uiZorderIdxInPart, uiPartDepth );  pcCU->deriveLeftBottomIdxAdi  ( uiPartIdxLB,              uiZorderIdxInPart, uiPartDepth );    iUnitSize      = g_uiMaxCUWidth >> g_uiMaxCUDepth;  iNumUnitsInCu  = uiCuWidth / iUnitSize;  iTotalUnits    = (iNumUnitsInCu << 2) + 1; // Top + RightTop + Left + LeftBottom + LeftTop = iNumUnitsInCu + iNumUnitsInCu + iNumUnitsInCu + iNumUnitsInCu + 1  //! 扫描顺序是从左下到左上，再从左上到右上  bNeighborFlags[iNumUnitsInCu*2] = isAboveLeftAvailable( pcCU, uiPartIdxLT );  iNumIntraNeighbor  += (Int)(bNeighborFlags[iNumUnitsInCu*2]);  iNumIntraNeighbor  += isAboveAvailable     ( pcCU, uiPartIdxLT, uiPartIdxRT, bNeighborFlags+(iNumUnitsInCu*2)+1 );  iNumIntraNeighbor  += isAboveRightAvailable( pcCU, uiPartIdxLT, uiPartIdxRT, bNeighborFlags+(iNumUnitsInCu*3)+1 );  iNumIntraNeighbor  += isLeftAvailable      ( pcCU, uiPartIdxLT, uiPartIdxLB, bNeighborFlags+(iNumUnitsInCu*2)-1 );  iNumIntraNeighbor  += isBelowLeftAvailable ( pcCU, uiPartIdxLT, uiPartIdxLB, bNeighborFlags+ iNumUnitsInCu   -1 );    bAbove = true;  bLeft  = true;  uiWidth=uiCuWidth2+1;  uiHeight=uiCuHeight2+1;    if (((uiWidth<<2)>iOrgBufStride)||((uiHeight<<2)>iOrgBufHeight))  {    return;  }  //! piRoiOrigin指向当前PU左上角  piRoiOrigin = pcCU->getPic()->getPicYuvRec()->getLumaAddr(pcCU->getAddr(), pcCU->getZorderIdxInCU()+uiZorderIdxInPart);  piAdiTemp   = piAdiBuf;  fillReferenceSamples ( pcCU, piRoiOrigin, piAdiTemp, bNeighborFlags, iNumIntraNeighbor, iUnitSize, iNumUnitsInCu, iTotalUnits, uiCuWidth, uiCuHeight, uiWidth, uiHeight, iPicStride, bLMmode);    Int   i;  // generate filtered intra prediction samples  Int iBufSize = uiCuHeight2 + uiCuWidth2 + 1;  // left and left above border + above and above right border + top left corner = length of 3. filter buffer  UInt uiWH = uiWidth * uiHeight;               // number of elements in one buffer  //! 下面所进行的工作主要是对参考样点进行3抽头的滤波。piAdiBuf指向滤波前的参考样点的首地址，在滤波前，先将所有参考样点  //! 拷贝到piFilterBuf指向的区域，经滤波后的样点值保存在piFilterBufN指向的区域，最终将滤波后的样点值拷贝到piFilterBuf1  //! 值得一提的是，最终的结果是，piAdiBuf指向的区域是未经滤波的样点值，而piFilterBuf1指向的区域是经过滤波的样点值，  //! 两者的地址相差uiWH = uiWidth * uiHeight = (uiCuWidth2 + 1) * (uiCuHeight2 + 1)，这就解释了在进行真正的帧内预测时，  //! 在需要滤波时，指向piAdiBuf的指针需要加上uiWH的偏移量  Int* piFilteredBuf1 = piAdiBuf + uiWH;        // 1. filter buffer  Int* piFilteredBuf2 = piFilteredBuf1 + uiWH;  // 2. filter buffer  Int* piFilterBuf = piFilteredBuf2 + uiWH;     // buffer for 2. filtering (sequential)  Int* piFilterBufN = piFilterBuf + iBufSize;   // buffer for 1. filtering (sequential) //!<存放的是参考样点经3抽头滤波后的值  // draft 8.4.4.2.3 Filtering process of neighbouring samples  Int l = 0;  // left border from bottom to top  for (i = 0; i < uiCuHeight2; i++)  {    piFilterBuf[l++] = piAdiTemp[uiWidth * (uiCuHeight2 - i)]; //!< 左边界，存储顺序为从下往上  }  // top left corner  piFilterBuf[l++] = piAdiTemp[0];  //!< 左上边界  // above border from left to right  for (i=0; i < uiCuWidth2; i++)  {    piFilterBuf[l++] = piAdiTemp[1 + i];  //!<上边界，存储顺序为从左往右  }  // 1. filtering with [1 2 1]  piFilterBufN[0] = piFilterBuf[0]; //!< 第1个点直接保存，不滤波  piFilterBufN[iBufSize - 1] = piFilterBuf[iBufSize - 1]; //!< 最后一个点也直接保存，不滤波  for (i = 1; i < iBufSize - 1; i++) //!< 对中间样点值进行3抽头[1 2 1] / 4 的平滑滤波  {    piFilterBufN[i] = (piFilterBuf[i - 1] + 2 * piFilterBuf[i]+piFilterBuf[i + 1] + 2) >> 2;  }  // fill 1. filter buffer with filtered values  l=0;  for (i = 0; i < uiCuHeight2; i++)  {    piFilteredBuf1[uiWidth * (uiCuHeight2 - i)] = piFilterBufN[l++];  // left border from bottom to top //!< 左边界  }  piFilteredBuf1[0] = piFilterBufN[l++]; //!< 左上边界  for (i = 0; i < uiCuWidth2; i++)  {    piFilteredBuf1[1 + i] = piFilterBufN[l++]; // above border from left to right //!< 上边界  }}

最后附上图，以帮助大家更好地理解代码，我就不对图多作解释了，相信大家对着代码能比较容易看明白的。

 （注，上图中，uiWidth和uiHeight实际上对应的是代码中的uiCUWidth和uiCUHeight，因画图的时候发生了遗漏，特此说明）

转自（http://blog.csdn.net/hevc_cjl/article/details/8184276）