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。
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Void TComPattern::initAdiPattern( TComDataCU* pcCU, UInt uiZorderIdxInPart, UInt uiPartDepth, Int* piAdiBuf, Int iOrgBufStride, Int iOrgBufHeight, Bool& bAbove, Bool& bLeft, Bool bLMmode )
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{//! bLMmode is usually false
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Pel* piRoiOrigin;
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Int* piAdiTemp;
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UInt uiCuWidth = pcCU->getWidth(0) >> uiPartDepth; //!< CU的宽度
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UInt uiCuHeight = pcCU->getHeight(0)>> uiPartDepth; //!< CU的高度
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UInt uiCuWidth2 = uiCuWidth<<1;
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UInt uiCuHeight2 = uiCuHeight<<1;
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UInt uiWidth;
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UInt uiHeight;
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Int iPicStride = pcCU->getPic()->getStride();
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Int iUnitSize = 0;
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Int iNumUnitsInCu = 0;
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Int iTotalUnits = 0;
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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
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Int iNumIntraNeighbor = 0; //!< 给可用邻块进行计数
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UInt uiPartIdxLT, uiPartIdxRT, uiPartIdxLB;
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//! 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
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pcCU->deriveLeftRightTopIdxAdi( uiPartIdxLT, uiPartIdxRT, uiZorderIdxInPart, uiPartDepth );
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pcCU->deriveLeftBottomIdxAdi ( uiPartIdxLB, uiZorderIdxInPart, uiPartDepth );
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iUnitSize = g_uiMaxCUWidth >> g_uiMaxCUDepth;
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iNumUnitsInCu = uiCuWidth / iUnitSize;
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iTotalUnits = (iNumUnitsInCu << 2) + 1; // Top + RightTop + Left + LeftBottom + LeftTop = iNumUnitsInCu + iNumUnitsInCu + iNumUnitsInCu + iNumUnitsInCu + 1
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//! 扫描顺序是从左下到左上，再从左上到右上
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bNeighborFlags[iNumUnitsInCu*2] = isAboveLeftAvailable( pcCU, uiPartIdxLT );
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iNumIntraNeighbor += (Int)(bNeighborFlags[iNumUnitsInCu*2]);
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iNumIntraNeighbor += isAboveAvailable ( pcCU, uiPartIdxLT, uiPartIdxRT, bNeighborFlags+(iNumUnitsInCu*2)+1 );
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iNumIntraNeighbor += isAboveRightAvailable( pcCU, uiPartIdxLT, uiPartIdxRT, bNeighborFlags+(iNumUnitsInCu*3)+1 );
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iNumIntraNeighbor += isLeftAvailable ( pcCU, uiPartIdxLT, uiPartIdxLB, bNeighborFlags+(iNumUnitsInCu*2)-1 );
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iNumIntraNeighbor += isBelowLeftAvailable ( pcCU, uiPartIdxLT, uiPartIdxLB, bNeighborFlags+ iNumUnitsInCu -1 );
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bAbove = true;
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bLeft = true;
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uiWidth=uiCuWidth2+1;
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uiHeight=uiCuHeight2+1;
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if (((uiWidth<<2)>iOrgBufStride)||((uiHeight<<2)>iOrgBufHeight))
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{
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return;
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}
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//! piRoiOrigin指向当前PU左上角
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piRoiOrigin = pcCU->getPic()->getPicYuvRec()->getLumaAddr(pcCU->getAddr(), pcCU->getZorderIdxInCU()+uiZorderIdxInPart);
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piAdiTemp = piAdiBuf;
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fillReferenceSamples ( pcCU, piRoiOrigin, piAdiTemp, bNeighborFlags, iNumIntraNeighbor, iUnitSize, iNumUnitsInCu, iTotalUnits, uiCuWidth, uiCuHeight, uiWidth, uiHeight, iPicStride, bLMmode);
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Int i;
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// generate filtered intra prediction samples
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Int iBufSize = uiCuHeight2 + uiCuWidth2 + 1; // left and left above border + above and above right border + top left corner = length of 3. filter buffer
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UInt uiWH = uiWidth * uiHeight; // number of elements in one buffer
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//! 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
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//! 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
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//! 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，
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//! 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，
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//! 在需要滤波时，指向piAdiBuf的指针需要加上uiWH的偏移量
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Int* piFilteredBuf1 = piAdiBuf + uiWH; // 1. filter buffer
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Int* piFilteredBuf2 = piFilteredBuf1 + uiWH; // 2. filter buffer
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Int* piFilterBuf = piFilteredBuf2 + uiWH; // buffer for 2. filtering (sequential)
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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
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// draft 8.4.4.2.3 Filtering process of neighbouring samples
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Int l = 0;
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// left border from bottom to top
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for (i = 0; i < uiCuHeight2; i++)
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{
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piFilterBuf[l++] = piAdiTemp[uiWidth * (uiCuHeight2 - i)]; //!< 左边界，存储顺序为从下往上
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}
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// top left corner
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piFilterBuf[l++] = piAdiTemp[0]; //!< 左上边界
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// above border from left to right
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for (i=0; i < uiCuWidth2; i++)
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{
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piFilterBuf[l++] = piAdiTemp[1 + i]; //!<上边界，存储顺序为从左往右
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}
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// 1. filtering with [1 2 1]
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piFilterBufN[0] = piFilterBuf[0]; //!< 第1个点直接保存，不滤波
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piFilterBufN[iBufSize - 1] = piFilterBuf[iBufSize - 1]; //!< 最后一个点也直接保存，不滤波
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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
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{
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piFilterBufN[i] = (piFilterBuf[i - 1] + 2 * piFilterBuf[i]+piFilterBuf[i + 1] + 2) >> 2;
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}
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// fill 1. filter buffer with filtered values
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l=0;
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for (i = 0; i < uiCuHeight2; i++)
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{
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piFilteredBuf1[uiWidth * (uiCuHeight2 - i)] = piFilterBufN[l++]; // left border from bottom to top //!< 左边界
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}
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piFilteredBuf1[0] = piFilterBufN[l++]; //!< 左上边界
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for (i = 0; i < uiCuWidth2; i++)
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{
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piFilteredBuf1[1 + i] = piFilterBufN[l++]; // above border from left to right //!< 上边界
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}
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}
复制代码
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。
[img][/img]
（转载请注明出处。原文地址：http://blog.csdn.net/hevc_cjl/article/details/8184276） |
