参考提案：JVET-D0040，JVET-F1003 （http://phenix.int-evry.fr/jvet/）

WS-PSNR相较于PSNR的改进之处在于，它在计算块失真时考虑了块在当前图像中的纬度信息，原文是“Calculate PSNR based on all samples; the distortion is weighted by sample area on corresponding spherical surface”.

WS-PSNR对应的代码在项目Tlib360中的TWSPSNRMetricCalc.h和TWSPSNRMetricCalc.cpp中

先分析TWSPSNRMetricCalc.h

class TWSPSNRMetric
{
private:Bool      m_bEnabled;Double    m_dWSPSNR[3];Int       m_outputBitDepth[MAX_NUM_CHANNEL_TYPE];         ///< bit-depth of output fileInt       m_referenceBitDepth[MAX_NUM_CHANNEL_TYPE];      ///< bit-depth of reference file//各投影格式权重，Y：亮度权重，C：色度权重Double* m_fErpWeight_Y;Double* m_fErpWeight_C;Double* m_fCubeWeight_Y;Double* m_fCubeWeight_C;Double* m_fEapWeight_Y;Double* m_fEapWeight_C;Double* m_fOctaWeight_Y;Double* m_fOctaWeight_C;Double* m_fIcoWeight_Y;Double* m_fIcoWeight_C;
#if SVIDEO_WSPSNR_SSPDouble* m_fSspWeight_Y;Double* m_fSspWeight_C;
#endifInt     m_codingGeoType;      //编码几何类型Int     m_iCodingFaceWidth;       //编码面宽度Int     m_iCodingFaceHeight;      //编码面高度Int     m_iChromaSampleLocType;       //采样色度格式
#if SVIDEO_WSPSNR_E2E//for E2E WS-PSNR calculation;
#if !SVIDEO_E2E_METRICSTVideoIOYuv *m_pcTVideoIOYuvInputFile;  //note: reference;TGeometry   *m_pRefGeometry;TGeometry   *m_pRecGeometry;TComPicYuv  *m_pcOrgPicYuv;TComPicYuv  *m_pcRecPicYuv;             //in original geometry domain;
#endif
#if !SVIDEO_E2E_METRICSInt         m_iLastFrmPOC;UInt        m_temporalSubsampleRatio;Int         m_iInputWidth;Int         m_iInputHeight;ChromaFormat m_inputChromaFomat;
#endif
#endif
public:TWSPSNRMetric();virtual ~TWSPSNRMetric();Bool    getWSPSNREnabled()  { return m_bEnabled; }        //获取m_bEnabledVoid    setWSPSNREnabledFlag(Bool bEnabledFlag)  { m_bEnabled = bEnabledFlag; }       //设置m_bEnabledVoid    setOutputBitDepth(Int iOutputBitDepth[MAX_NUM_CHANNEL_TYPE]);     //输出图像bit深度Void    setReferenceBitDepth(Int iReferenceBitDepth[MAX_NUM_CHANNEL_TYPE]);       //参考图像bit深度//设置视频几何信息Void    setCodingGeoInfo(SVideoInfo& sVidInfo, Int iChromaSampleLocType) { m_codingGeoType = sVidInfo.geoType; m_iCodingFaceWidth = sVidInfo.iFaceWidth; m_iCodingFaceHeight = sVidInfo.iFaceHeight; m_iChromaSampleLocType =iChromaSampleLocType; }
#if SVIDEO_WSPSNR_E2E
#if SVIDEO_E2E_METRICSVoid    setCodingGeoInfo2(SVideoInfo& sRefVideoInfo, SVideoInfo& sRecVideoInfo, InputGeoParam *pInGeoParam);Void    xCalculateE2EWSPSNR(TComPicYuv *pcRecPicYuv, TComPicYuv *pcOrigPicYuv);
#elseVoid    setCodingGeoInfo2(SVideoInfo& sRefVideoInfo, SVideoInfo& sRecVideoInfo, InputGeoParam *pInGeoParam, TVideoIOYuv& yuvInputFile, Int iInputWidth, Int iInputHeight, UInt tempSubsampleRatio);Void    xCalculateE2EWSPSNR(TComPicYuv *pcPicD, Int iPOC);
#endif
#endifDouble* getWSPSNR() {return m_dWSPSNR;}       //获取WS-PSNRVoid    createTable(TComPicYuv* pcPicD, TGeometry *pcCodingGeomtry);      //创建投影格式对应的权重列表Void    xCalculateWSPSNR( TComPicYuv* pcOrgPicYuv, TComPicYuv* pcPicD );      //计算WS-PSNR//inline Int round(POSType t) { return (Int)(t+ (t>=0? 0.5 :-0.5)); };
};

再分析 TWSPSNRMetricCalc.cpp中的函数，这个cpp文件中除去构造、析构、以及setCodingGeoInfo2()外，只剩下如下两个函数。

void TWSPSNRMetric::createTable()：创建投影格式对应的权重列表。这里只截取了最常用的ERP和CMP对应的部分。每一种投影格式都对应一种权重，可以看到ERP的权重只与高度位置相关，CMP的权重与所在面的x,y坐标位置相关。

void TWSPSNRMetric::createTable(TComPicYuv* pcPicD, TGeometry *pcCodingGeomtry)
{if(!m_bEnabled){return;}SVideoInfo *pCodingSVideoInfo = pcCodingGeomtry->getSVideoInfo();Int iFaceWidth = pCodingSVideoInfo->iFaceWidth;Int iFaceHeight = pCodingSVideoInfo->iFaceHeight;Int iScaleX = pcPicD->getComponentScaleX(COMPONENT_Cb);Int iScaleY = pcPicD->getComponentScaleY(COMPONENT_Cb);Double dChromaOffset[2] = {0.0, 0.0}; //[0: X; 1: Y];if(pcPicD->getChromaFormat() == CHROMA_420){dChromaOffset[0] = (m_iChromaSampleLocType == 0 || m_iChromaSampleLocType == 2)? 0 : 0.5;dChromaOffset[1] = (m_iChromaSampleLocType == 2 || m_iChromaSampleLocType == 3)? 0 : 0.5;}//ERP投影if(pcCodingGeomtry->getType()==SVIDEO_EQUIRECT){Double fWeightSum_Y=0;Double fWeightSum_C=0;Int   iWidth = pcPicD->getWidth(COMPONENT_Y) ;      //获取亮度宽度Int   iHeight = pcPicD->getHeight(COMPONENT_Y) ;    //获取亮度高度Int   iWidthC = pcPicD->getWidth(COMPONENT_Cb) ;        //获取色度宽度Int   iHeightC = pcPicD->getHeight(COMPONENT_Cb) ;  //获取色度高度m_fErpWeight_Y=(Double*)malloc(iHeight*sizeof(Double));     //亮度权重和高度有关m_fErpWeight_C=(Double*)malloc(iHeightC*sizeof(Double));        //色度权重和高度有关//计算亮度和色度的纬度权重for(Int y=0; y< iHeight; y++){m_fErpWeight_Y[y]=scos((y-(iHeight/2-0.5))*S_PI/iHeight); //F1003 公式(72)，计算亮度权重fWeightSum_Y += m_fErpWeight_Y[y];}for(Int y=0; y< iHeightC; y++){m_fErpWeight_C[y]=scos(((y<<iScaleY)+dChromaOffset[1]+0.5-iHeight/2)*S_PI/iHeight);  //F1003 公式(72)，计算色度权重fWeightSum_C += m_fErpWeight_C[y];}for(Int y=0; y< iHeight; y++){m_fErpWeight_Y[y]=m_fErpWeight_Y[y]/fWeightSum_Y/iWidth;}for(Int y=0; y< iHeightC; y++){m_fErpWeight_C[y]=m_fErpWeight_C[y]/fWeightSum_C/(iWidthC);}}//CMP投影else if(pcCodingGeomtry->getType()==SVIDEO_CUBEMAP){Double fWeightSum_Y=0;Double fWeightSum_C=0;    //亮度、色度权重和面的高度宽度都有关m_fCubeWeight_Y=(Double*)malloc(iFaceHeight * iFaceWidth*sizeof(Double));       m_fCubeWeight_C=(Double*)malloc((iFaceHeight >> iScaleY) * (iFaceWidth >> iScaleX)*sizeof(Double));//计算亮度和色度权重for(Int y = 0; y < iFaceHeight; y++ ){for(Int x=0; x < iFaceWidth; x++){Int ci, cj, r2;Double d2;ci= iFaceWidth/2;cj= iFaceHeight/2;d2 = (x+0.5-ci)*(x+0.5-ci)+(y+0.5-cj)*(y+0.5-cj);r2 = (iFaceWidth/2)*(iFaceWidth/2);Double weight= 1.0/((1+d2/r2)*ssqrt(1.0*(1+d2/r2)));m_fCubeWeight_Y[iFaceWidth*y+x] = weight;fWeightSum_Y += weight;}}for(Int y = 0; y < iFaceHeight; y++ ){for(Int x=0; x<iFaceWidth; x++){m_fCubeWeight_Y[iFaceHeight*y+x] = (m_fCubeWeight_Y[iFaceHeight*y+x])/fWeightSum_Y/6.0;}}for(Int y = 0; y < (iFaceHeight>>iScaleY); y++ ){for(Int x=0; x< (iFaceWidth>>iScaleX); x++){Int ci, cj, r2;Double d2;ci= iFaceWidth/2;cj= iFaceHeight/2;d2 = (x*(1<<iScaleX)+dChromaOffset[0]+0.5 - ci)*(x*(1<<iScaleX)+dChromaOffset[0]+0.5 - ci) + (y*(1<<iScaleY)+dChromaOffset[1]+0.5 -cj)*(y*(1<<iScaleY)+dChromaOffset[1]+0.5 -cj);r2 = (iFaceWidth/2)*(iFaceWidth/2);Double weight= 1.0/((1+d2/r2)*sqrt(1.0*(1+d2/r2)));m_fCubeWeight_C[(iFaceWidth>>iScaleX)*y+x]=weight;fWeightSum_C += weight;}}for(Int y = 0; y < (iFaceHeight>>iScaleY); y++ ){for(Int x=0; x< (iFaceWidth>>iScaleX); x++){m_fCubeWeight_C[(iFaceWidth>>iScaleX)*y+x]=(m_fCubeWeight_C[(iFaceWidth>>iScaleX)*y+x])/fWeightSum_C/6.0;}}}
}

Void TWSPSNRMetric::xCalculateWSPSNR()

Void TWSPSNRMetric::xCalculateWSPSNR( TComPicYuv* pcOrgPicYuv, TComPicYuv* pcPicD )
{//初始化亮度色度bit信息Int iBitDepthForPSNRCalc[MAX_NUM_CHANNEL_TYPE];Int iReferenceBitShift[MAX_NUM_CHANNEL_TYPE];Int iOutputBitShift[MAX_NUM_CHANNEL_TYPE];iBitDepthForPSNRCalc[CHANNEL_TYPE_LUMA] = std::max(m_outputBitDepth[CHANNEL_TYPE_LUMA], m_referenceBitDepth[CHANNEL_TYPE_LUMA]);iBitDepthForPSNRCalc[CHANNEL_TYPE_CHROMA] = std::max(m_outputBitDepth[CHANNEL_TYPE_CHROMA], m_referenceBitDepth[CHANNEL_TYPE_CHROMA]);iReferenceBitShift[CHANNEL_TYPE_LUMA] = iBitDepthForPSNRCalc[CHANNEL_TYPE_LUMA] - m_referenceBitDepth[CHANNEL_TYPE_LUMA];iReferenceBitShift[CHANNEL_TYPE_CHROMA] = iBitDepthForPSNRCalc[CHANNEL_TYPE_CHROMA] - m_referenceBitDepth[CHANNEL_TYPE_CHROMA];iOutputBitShift[CHANNEL_TYPE_LUMA] = iBitDepthForPSNRCalc[CHANNEL_TYPE_LUMA] - m_outputBitDepth[CHANNEL_TYPE_LUMA];iOutputBitShift[CHANNEL_TYPE_CHROMA] = iBitDepthForPSNRCalc[CHANNEL_TYPE_CHROMA] - m_outputBitDepth[CHANNEL_TYPE_CHROMA];memset(m_dWSPSNR, 0, sizeof(Double)*3);TComPicYuv &picd=*pcPicD;//Double SSDspsnr[3]={0, 0 ,0};//ChromaFormat chromaFormat = pcPicD->getChromaFormat();for(Int chan=0; chan<pcPicD->getNumberValidComponents(); chan++){const ComponentID ch=ComponentID(chan);const Pel*  pOrg       = pcOrgPicYuv->getAddr(ch);const Int   iOrgStride = pcOrgPicYuv->getStride(ch);const Pel*  pRec       = picd.getAddr(ch);const Int   iRecStride = picd.getStride(ch);const Int   iWidth  = pcPicD->getWidth (ch) ;const Int   iHeight = pcPicD->getHeight(ch) ;Double fWeight =1;Double fWeightSum=0;//Int   iSize   = iWidth*iHeight;Double SSDwpsnr=0;//WS-PSNRfor(Int y = 0; y < iHeight; y++ )   //得到宽高后，对每一个点的失真进行统计{//ERP格式只与高度有关if (m_codingGeoType==SVIDEO_EQUIRECT){      if(!chan)   //亮度{fWeight=m_fErpWeight_Y[y];}else        //色度{fWeight=m_fErpWeight_C[y];}}for(Int x = 0; x < iWidth; x++ ) {//参考图像和输出图像差值Intermediate_Int iDiff = (Intermediate_Int)( (pOrg[x]<<iReferenceBitShift[toChannelType(ch)]) - (pRec[x]<<iOutputBitShift[toChannelType(ch)]) );//CMP格式和x,y都有关if (m_codingGeoType==SVIDEO_CUBEMAP){if(!chan){if(iWidth/4 == iHeight/3 && x >= iWidth/4 && (y< iHeight/3 || y>= 2*iHeight/3)){fWeight=0;}else {fWeight=m_fCubeWeight_Y[(m_iCodingFaceWidth)*(y%(m_iCodingFaceHeight)) +(x%(m_iCodingFaceWidth))];}}else{if(iWidth/4 == iHeight/3 && x >= iWidth/4 && (y< iHeight/3 || y>= 2*iHeight/3)){fWeight=0;}else{fWeight=m_fCubeWeight_C[(m_iCodingFaceWidth>>(pcPicD->getComponentScaleX(COMPONENT_Cb)))*(y%(m_iCodingFaceHeight>>(pcPicD->getComponentScaleY(COMPONENT_Cb)))) +(x%(m_iCodingFaceWidth>>(pcPicD->getComponentScaleX(COMPONENT_Cb))))];}  }}if(fWeight>0)fWeightSum += fWeight;SSDwpsnr   += iDiff * iDiff*fWeight;        //引入了fWeight，即对每个点的失真进行一个权重处理。最终得到总的SSD}pOrg += iOrgStride;pRec += iRecStride;}const Int maxval = 255<<(iBitDepthForPSNRCalc[toChannelType(ch)]-8) ;//const Double fRefValue = (Double) maxval * maxval * iSize;m_dWSPSNR[ch]         = ( SSDwpsnr ? 10.0 * log10( (maxval * maxval*fWeightSum) / (Double)SSDwpsnr ) : 999.99 );        //计算PSNR}}