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UMHexagonS搜索过程

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通过相邻块的预测得到mvp后,会以mvp为基础搜索最佳的匹配块,UMHexagonS就是h.264中用的一种搜索算法。

UMHexagonS是一种整像素搜索算法,也就是搜索过程中,参考图像一直都是原来的重构图像,并没有使用经过插值的图像进行搜索。

 

首先UMHexagonS会根据相关信息去得到比较有可能的mv,(然后用小菱形搜索到该区域去搜索该区域中的最佳mv,这种情况会在下面注明)

由于UMHexagonS是一种整像素搜索算法,所以会存在对分数的mv取整的情况,此时取整是指把mv对齐到某个像素上,消去分数部分

1.mvp取整后得到的mv(然后采用小菱形搜索)

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2.原点,mv为0,即当前块的位置(然后采用小菱形搜索)

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3.上层块mv,如果当前块为8x8,那么覆盖当前块的16x8块就是其上层块

   运动搜索中,分块模式有7种

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   模式4的上层模式为2,模式7的上层模式为4

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4.共同位置块mv,取上一参考图像与当前块相同位置的块的mv,然后取整

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5.共同位置参考mv通过参考图像距离计算后得到的mv,然后取整

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6.最后还采用一次小菱形搜索,主要为了对上面3、4、5预测后得到的最佳mv再采用一次小菱形搜索以得到该区域内最佳mv

   小菱形搜索就是把mv的x,y分别+1,-1后得到的新mv,然后各自对比得到其中最优的mv

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在做完上方的整像素mv预测后,需要计算该mv的匹配满意程度,以跳转做不同的后续搜索处理,该过程叫Early Termination。

Early Termination由于涉及到数学上的分析,所以会在后面的章节再细述。

Early Termination有两个个跳转出口,分别代表不同的匹配满意程度:

  • Extended Hexagon-based Search(六边形模板反复搜索)               满意
  • the third step with a small search pattern(小菱形模板反复搜索)   很满意

但是如果在不甚满意的情况下,Early Termination会不作跳转,直接执行下一步

 

经过上面的整像素mv预测后,得到其中最佳的整像素mv,如果该mv经Early Termination判断为不甚满意,会以该mv为中心,直接开始UMH搜索

1.Unsymmetrical-cross search(非对称十字搜索)

   非对称十字搜索会先后对x轴与y轴进行搜索,y轴的搜索范围是x轴的一半,这是因为在一般的视频中,镜头的纵向移动距离会比较短,横向移动距离会比较长,而且比较常见。搜索时,横轴的搜索范围是search range,而纵轴会是它的一般。

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2.Spiral search(螺旋搜索)

   螺旋搜索采用的是full search(全搜索)的搜索方法,但是搜索步长只有24,相当于5x5的区域。而全搜索会对整个搜索范围进行搜索。

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3.Uneven Multi-Hexagon-grid Search(不规律六边形模板搜索)

   这种搜索方式是以当前mv指向的像素点为圆心,一圈一圈地往外搜索,一旦在某个圈内搜索到更佳的位置,立刻停止搜索,否则搜索完整个搜索范围

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4.Extended Hexagon-based Search(六边形模板反复搜索)

   不同于上一个搜索方式,这种搜索方式是以当前最佳mv指向的像素点为圆心,进行一次六边形模板搜索,一旦搜索到某个更佳的位置,则以此位置为圆心,重新进行一次六边形模板搜索。如果没有比圆心更佳的位置,则终止搜索。

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5.the third step with a small search pattern(小菱形模板反复搜索)

   类似Extended Hexagon-based Search(六边形模板反复搜索)的搜索方式,不过把六边形换成了菱形

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以上可参照jvt-G016 

JM8.6

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/*!
 ************************************************************************
 * \brief用非对称十字形多层次六边形格点搜索算法进行运动搜索
 *    FastIntegerPelBlockMotionSearch: fast pixel block motion search 
 *    this algrithm is called UMHexagonS(see JVT-D016),which includes 
 *    four steps with different kinds of search patterns
 * \par Input:
 * pel_t**   orig_pic,     // <--  original picture
 * int       ref,          // <--  reference frame (0... or -1 (backward))
 * int       pic_pix_x,    // <--  absolute x-coordinate of regarded AxB block
 * int       pic_pix_y,    // <--  absolute y-coordinate of regarded AxB block
 * int       blocktype,    // <--  block type (1-16x16 ... 7-4x4)
 * int       pred_mv_x,    // <--  motion vector predictor (x) in sub-pel units
 * int       pred_mv_y,    // <--  motion vector predictor (y) in sub-pel units
 * int*      mv_x,         //  --> motion vector (x) - in pel units
 * int*      mv_y,         //  --> motion vector (y) - in pel units
 * int       search_range, // <--  1-d search range in pel units                         
 * int       min_mcost,    // <--  minimum motion cost (cost for center or huge value)
 * double    lambda        // <--  lagrangian parameter for determining motion cost
 * \par
 * Three macro definitions defined in this program:
 * 1. EARLY_TERMINATION: early termination algrithm, refer to JVT-D016.doc
 * 2. SEARCH_ONE_PIXEL: search one pixel in search range
 * 3. SEARCH_ONE_PIXEL1(value_iAbort): search one pixel in search range,
 *                                 but give a parameter to show if mincost refeshed
 * \ Main contributors: (see contributors.h for copyright, address and affiliation details)
 *   Zhibo Chen         <chenzhibo@tsinghua.org.cn>
 *   JianFeng Xu        <fenax@video.mdc.tsinghua.edu.cn>  
 * \date   : 2003.8
 ************************************************************************
 */
int                                     //  ==> minimum motion cost after search
FastIntegerPelBlockMotionSearch  (pel_t**   orig_pic,     // <--  not used
                  int       ref,          // <--  reference frame (0... or -1 (backward))
                  int       list,
                  int       pic_pix_x,    // <--  absolute x-coordinate of regarded AxB block
                  int       pic_pix_y,    // <--  absolute y-coordinate of regarded AxB block
                  int       blocktype,    // <--  block type (1-16x16 ... 7-4x4)
                  int       pred_mv_x,    // <--  motion vector predictor (x) in sub-pel units MV_pred_space 中值预测矢量
                  int       pred_mv_y,    // <--  motion vector predictor (y) in sub-pel units
                  int*      mv_x,         /* --> motion vector (x) - in pel units 
                                      按照H.264标准算法进行的运动矢量预测得到MV_pred 
                                      指的是SetMotionVectorPreditor函数预测的MV
                                      和中值预测的区别在于SetMotionVectorPreditor函数预测的MV的参考邻块和当前块必须参
                                      考同一个参考帧,而中值预测的邻块则没有这个要求,二者可能一样,也可能不同*/
                  int*      mv_y,         //  --> motion vector (y) - in pel units
                  int       search_range, // <--  1-d search range in pel units                         
                  int       min_mcost,    // <--  minimum motion cost (cost for center or huge value)
                  double    lambda)       // <--  lagrangian parameter for determining motion cost
{
  static int Diamond_x[4] = {-1, 0, 1, 0};//对应不同算法  菱形插值
  static int Diamond_y[4] = {0, 1, 0, -1};
  static int Hexagon_x[6] = {2, 1, -1, -2, -1, 1};//六角形插值
  static int Hexagon_y[6] = {0, -2, -2, 0,  2, 2};
  static int Big_Hexagon_x[16] = {0,-2, -4,-4,-4, -4, -4, -2,  0,  2,  4,  4, 4, 4, 4, 2};
  static int Big_Hexagon_y[16] = {4, 3, 2,  1, 0, -1, -2, -3, -4, -3, -2, -1, 0, 1, 2, 3};//大六角形插值

  int   pos, cand_x, cand_y,  mcost;
  pel_t *(*get_ref_line)(int, pel_t*, int, int, int, int);
  int   list_offset   = ((img->MbaffFrameFlag)&&(img->mb_data[img->current_mb_nr].mb_field))? img->current_mb_nr%2 ? 4 : 2 : 0;
  pel_t*  ref_pic       = listX[list+list_offset][ref]->imgY_11;//img->type==B_IMG? Refbuf11 [ref+((mref==mref_fld)) +1] : Refbuf11[ref];
  int   best_pos      = 0;                                        // position with minimum motion cost
  int   max_pos       = (2*search_range+1)*(2*search_range+1);    // number of search positions
  int   lambda_factor = LAMBDA_FACTOR (lambda);                   // factor for determining lagragian motion cost
  int   mvshift       = 2;                  // motion vector shift for getting sub-pel units
  int   blocksize_y   = input->blc_size[blocktype][1];            // vertical block size
  int   blocksize_x   = input->blc_size[blocktype][0];            // horizontal block size
  int   blocksize_x4  = blocksize_x >> 2;                         // horizontal block size in 4-pel units
  int   pred_x        = (pic_pix_x << mvshift) + pred_mv_x;       // predicted position x (in sub-pel units)
  int   pred_y        = (pic_pix_y << mvshift) + pred_mv_y;       // predicted position y (in sub-pel units)
  int   center_x      = pic_pix_x + *mv_x;                        // center position x (in pel units)
  int   center_y      = pic_pix_y + *mv_y;                        // center position y (in pel units)
  int    best_x, best_y;
  int   check_for_00  = (blocktype==1 && !input->rdopt && img->type!=B_SLICE && ref==0);
  int   search_step,iYMinNow, iXMinNow;
  int   i,m, iSADLayer; 
  int   iAbort;
  int       N_Bframe = input->successive_Bframe;
  float betaSec,betaThird;
  int height=((img->MbaffFrameFlag)&&(img->mb_data[img->current_mb_nr].mb_field))?img->height/2:img->height;
  

  //===== set function for getting reference picture lines =====
  if ((center_x > search_range) && (center_x < img->width -1-search_range-blocksize_x) &&
    (center_y > search_range) && (center_y < height-1-search_range-blocksize_y)   )
  {
    get_ref_line = FastLineX;
  }
  else
  {
    get_ref_line = UMVLineX;  //无运动矢量限制,需像素拓展
  }
  
  //////allocate memory for search state//////////////////////////
  //初始化搜索标记
  memset(McostState[0],0,(2*search_range+1)*(2*search_range+1)*4);
  
   ///////Threshold defined for early termination///////////////////  
  //为早期终止设定门限值
  if(ref>0) 
  {
    if(pred_SAD_ref!=0)
    {
      betaSec = Bsize[blocktype]/(pred_SAD_ref*pred_SAD_ref)-AlphaSec[blocktype];
      betaThird = Bsize[blocktype]/(pred_SAD_ref*pred_SAD_ref)-AlphaThird[blocktype];
    }
    else
    {
      betaSec = 0;
      betaThird = 0;
    }
  }
  else 
  {
    if(blocktype==1)
    {
      if(pred_SAD_space !=0)
      {
        betaSec = Bsize[blocktype]/(pred_SAD_space*pred_SAD_space)-AlphaSec[blocktype];
        betaThird = Bsize[blocktype]/(pred_SAD_space*pred_SAD_space)-AlphaThird[blocktype];
      }
      else
      {
        betaSec = 0;
        betaThird = 0;
      }
    }
    else
    {
      if(pred_SAD_uplayer !=0)
      {
        betaSec = Bsize[blocktype]/(pred_SAD_uplayer*pred_SAD_uplayer)-AlphaSec[blocktype];
        betaThird = Bsize[blocktype]/(pred_SAD_uplayer*pred_SAD_uplayer)-AlphaThird[blocktype];
      }
      else
      {
        betaSec = 0;
        betaThird = 0;
      }
    }
  }
  /*********检测中值预测矢量**************//*其实就是把得到的mv_pred取整得到的预测矢量*/
  //  MV_pred_space 中值预测矢量
  //check the center median predictor
  cand_x = center_x ;
  cand_y = center_y ;
  mcost = MV_COST (lambda_factor, mvshift, cand_x, cand_y, pred_x, pred_y);//通过计算候选mv所占用的bit得到mv_cost = lambda * bit_of_mv
  mcost = PartCalMad(ref_pic, orig_pic, get_ref_line,blocksize_y,blocksize_x,blocksize_x4,mcost,min_mcost,cand_x,cand_y);//cost = mv_cost + SAD
  McostState[search_range][search_range] = mcost;
  if (mcost < min_mcost)
  {
    min_mcost = mcost;
    best_x = cand_x;
    best_y = cand_y;
  }

  iXMinNow = best_x;
  iYMinNow = best_y;
  for (m = 0; m < 4; m++) //小菱形检测
  {   
    cand_x = iXMinNow + Diamond_x[m];
    cand_y = iYMinNow + Diamond_y[m];   
    SEARCH_ONE_PIXEL
  } 
/*****************原点检测***************************************/
  if(center_x != pic_pix_x || center_y != pic_pix_y)
  {
    cand_x = pic_pix_x ;    
    cand_y = pic_pix_y ;
    SEARCH_ONE_PIXEL

    iXMinNow = best_x;
    iYMinNow = best_y;
    for (m = 0; m < 4; m++)//小菱形检测
    {   
      cand_x = iXMinNow + Diamond_x[m]; 
      cand_y = iYMinNow + Diamond_y[m];   
      SEARCH_ONE_PIXEL
    } 
  }
 /**********************上层块预测矢量检测*********************************/ 
    if(blocktype>1)//
  {
    cand_x = pic_pix_x + (pred_MV_uplayer[0]/4);
    cand_y = pic_pix_y + (pred_MV_uplayer[1]/4);
    SEARCH_ONE_PIXEL
    if ((min_mcost-pred_SAD_uplayer)<pred_SAD_uplayer*betaThird)
      goto third_step;
    else if((min_mcost-pred_SAD_uplayer)<pred_SAD_uplayer*betaSec)
      goto sec_step;
  } 
    /****************相应块预测***************************************/

  //coordinate position prediction
  if ((img->number > 1 + ref && ref!=-1) || (list == 1 && (Bframe_ctr%N_Bframe) > 1))  //for debug
  {
    cand_x = pic_pix_x + pred_MV_time[0]/4;
    cand_y = pic_pix_y + pred_MV_time[1]/4;
    SEARCH_ONE_PIXEL
  }
  /******************相邻参考帧预测*********************************/

  //prediciton using mV of last ref moiton vector
  if (input->PicInterlace == FIELD_CODING)//场编码,用最近的场MV预测
  {
    if ((list==0 && ref > 0) || (img->type == B_SLICE && list == 0 && (ref==0 ||ref==2 ) )) 
      //Notes: for interlace case, ref==1 should be added
    {
      cand_x = pic_pix_x + pred_MV_ref[0]/4;
      cand_y = pic_pix_y + pred_MV_ref[1]/4;
      SEARCH_ONE_PIXEL
    }
  }
  else
  {   //多参考帧预测时,用另一帧的MV预测
    if ((list==0 && ref > 0) || (img->type == B_SLICE && list == 0 && ref==0 )) 
      //Notes: for interlace case, ref==1 should be added
    {
      cand_x = pic_pix_x + pred_MV_ref[0]/4;
      cand_y = pic_pix_y + pred_MV_ref[1]/4;
      SEARCH_ONE_PIXEL
    }
  }
  //small local search
  iXMinNow = best_x;
  iYMinNow = best_y;
  for (m = 0; m < 4; m++)//小菱形搜索
  {   
    cand_x = iXMinNow + Diamond_x[m];
    cand_y = iYMinNow + Diamond_y[m];   
    SEARCH_ONE_PIXEL
  } 

  //early termination algrithm, refer to JVT-D016
   //根据SAD值判断需要跳转的步骤,SAD较小时转到步骤3,较大时转到步骤2,很大时转到步骤1
    EARLY_TERMINATION
  
  if(blocktype>6)
    goto sec_step;
  else
    goto first_step;
  
first_step: //Unsymmetrical-cross search 不甚满意
  iXMinNow = best_x;
  iYMinNow = best_y;
  
  for(i=1;i<=search_range/2;i++)//水平方向搜索
  {
    search_step = 2*i - 1;
    cand_x = iXMinNow + search_step;
    cand_y = iYMinNow ;
    SEARCH_ONE_PIXEL    
    cand_x = iXMinNow - search_step;
    cand_y = iYMinNow ;
    SEARCH_ONE_PIXEL
  }

  //垂直方向搜索,注意垂直方向搜索点比水平方向少,考虑到了水平方向较垂直方向重要
  for(i=1;i<=search_range/4;i++)
  {
    search_step = 2*i - 1;
    cand_x = iXMinNow ;
    cand_y = iYMinNow + search_step;
    SEARCH_ONE_PIXEL
    cand_x = iXMinNow ;
    cand_y = iYMinNow - search_step;
    SEARCH_ONE_PIXEL
  }
  //early termination algrithm, refer to JVT-D016
    //在这里也进行中止、跳转检测,考虑到一般序列中含有大量水平、垂直方向的运动。
    EARLY_TERMINATION
  
  iXMinNow = best_x;
  iYMinNow = best_y;
    //螺旋搜索,类似全搜索法,只搜索前25点,相当于5×5区域全搜索
  for(pos=1;pos<25;pos++)
  {
    cand_x = iXMinNow + spiral_search_x[pos];
    cand_y = iYMinNow + spiral_search_y[pos];
    SEARCH_ONE_PIXEL
  }
  //early termination algrithm, refer to JVT-D016
    EARLY_TERMINATION

   // Uneven Multi-Hexagon-grid Search 
    //超六边形模板搜索,(多圈)
  for(i=1;i<=search_range/4; i++)
  {
    iAbort = 0;   
    for (m = 0; m < 16; m++)
    {
      cand_x = iXMinNow + Big_Hexagon_x[m]*i;
      cand_y = iYMinNow + Big_Hexagon_y[m]*i; 
      SEARCH_ONE_PIXEL1(1)
    }
    if (iAbort)
    { 
      //early termination algrithm, refer to JVT-D016
      EARLY_TERMINATION
    }
  }

// 六边形模板反复搜索(也可以用大菱形代替),搜索完后进入第三步骤
sec_step:  //Extended Hexagon-based Search 满意
      iXMinNow = best_x;
      iYMinNow = best_y;
      for(i=0;i<search_range;i++) 
      {
        iAbort = 1;   
        for (m = 0; m < 6; m++)
        {   
          cand_x = iXMinNow + Hexagon_x[m];
          cand_y = iYMinNow + Hexagon_y[m];   
          SEARCH_ONE_PIXEL1(0)
        } 
        if(iAbort)
          break;
        iXMinNow = best_x;
        iYMinNow = best_y;
      }
// 小菱形模板反复搜索,得到最终的运动矢量            
third_step: // the third step with a small search pattern  很满意
      iXMinNow = best_x;
      iYMinNow = best_y;
      for(i=0;i<search_range;i++) 
      {
        iSADLayer = 65536;
        iAbort = 1;   
        for (m = 0; m < 4; m++)
        {   
          cand_x = iXMinNow + Diamond_x[m];
          cand_y = iYMinNow + Diamond_y[m];   
          SEARCH_ONE_PIXEL1(0)
        } 
        if(iAbort)
          break;
        iXMinNow = best_x;
        iYMinNow = best_y;
      }

      *mv_x = best_x - pic_pix_x;
      *mv_y = best_y - pic_pix_y; 
      return min_mcost;
  }
View Code

 

 

UMHexagonS搜索过程,布布扣,bubuko.com

UMHexagonS搜索过程

标签:des   style   class   blog   code   http   

原文地址:http://www.cnblogs.com/TaigaCon/p/3788984.html

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