h.264全搜索以及快速全搜索算法

h.264全搜索以及快速全搜索算法

Full Search

全搜索算法是最简单暴力的一种搜索算法，对搜索范围内的所有像素点都进行匹配对比，选出最合适的运动向量，以下就是一个搜索范围为4的全搜索范围（单个像素点）

/*!************************************************************************ brief按照螺旋搜索顺序进行全搜索*    Full pixel block motion search*    目标是得到(mv_x,mv_y)和min_mcost，(mv_x,mv_y)指示从哪里开始做分像素搜索，search center*    后者用来跟分像素搜索结果做比较************************************************************************/
int                                               //  ==> minimum motion cost after search
FullPelBlockMotionSearch (pel_t**   orig_pic,     // <--  original pixel values for the AxB blockint       ref,          // <--  reference frame (0... or -1 (backward))int       list,int       pic_pix_x,    // <--  absolute x-coordinate of regarded AxB blockAxB宏块原点在图像中的绝对坐标int       pic_pix_y,    // <--  absolute y-coordinate of regarded AxB blockint       blocktype,    // <--  block type (1-16x16 ... 7-4x4)int       pred_mv_x,    // <--  motion vector predictor (x) in sub-pel unitsint       pred_mv_y,    // <--  motion vector predictor (y) in sub-pel unitsint*      mv_x,         // <--> in: search center (x) / out: motion vector (x) - in pel unitsint*      mv_y,         // <--> in: search center (y) / out: motion vector (y) - in pel unitsint       search_range, // <--  1-d search range in pel unitsint       min_mcost,    // <--  minimum motion cost (cost for center or huge value)double    lambda)       // <--  lagrangian parameter for determining motion cost
{int   pos, cand_x, cand_y, y, x4, mcost;pel_t *orig_line, *ref_line;pel_t *(*get_ref_line)(int, pel_t*, int, int, int, int);//
//参考帧偏移量 帧场自适应且宏块地址为偶数=4 帧场自适应宏块地址为奇数=2 非帧场自适应=0int   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;int   img_width     = listX[list+list_offset][ref]->size_x;int   img_height    = listX[list+list_offset][ref]->size_y;int   best_pos      = 0;                                        // position with minimum motion cost//计算最大需要搜索的位置个数int   max_pos       = (2*search_range+1)*(2*search_range+1);    // number of search positionsint   lambda_factor = LAMBDA_FACTOR (lambda);                   // factor for determining lagragian motion costint   blocksize_y   = input->blc_size[blocktype][1];            // vertical block sizeint   blocksize_x   = input->blc_size[blocktype][0];            // horizontal block sizeint   blocksize_x4  = blocksize_x >> 2;                         // horizontal block size in 4-pel unitsint   pred_x        = (pic_pix_x << 2) + pred_mv_x;       // predicted position x (in sub-pel units)1/4子像素为单位的预测MVint   pred_y        = (pic_pix_y << 2) + 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   check_for_00  = (blocktype==1 && !input->rdopt && img->type!=B_SLICE && ref==0);//===== set function for getting reference picture lines =====//通过判断搜索范围会不会出界，设置获取参考像素值的函数if ((center_x > search_range) && (center_x < img->width -1-search_range-blocksize_x) &&(center_y > search_range) && (center_y < img->height-1-search_range-blocksize_y)   ){get_ref_line = FastLineX;//未出界
  }else{get_ref_line = UMVLineX;//出界
  }//===== loop over all search positions =====//max_pos是搜索位置的个数,计算见上面for (pos=0; pos<max_pos; pos++){//--- set candidate position (absolute position in pel units) ---/*(center_x,center_y)是由预测MV估计出来的搜索中心，在以它为中心的范围内，对按照螺旋形顺序排列的候选点进行搜索，每个候选点都是一个可能参考块的左上角起始点*/cand_x = center_x + spiral_search_x[pos];//螺旋搜索cand_y = center_y + spiral_search_y[pos];//--- initialize motion cost (cost for motion vector) and check ---//计算MVD的代价，换算成四分之一像素(cand--candidate候选点)mcost = MV_COST (lambda_factor, 2, cand_x, cand_y, pred_x, pred_y);if (check_for_00 && cand_x==pic_pix_x && cand_y==pic_pix_y){//螺旋搜索到的点为原点,不过为什么是减去16bit?mcost -= WEIGHTED_COST (lambda_factor, 16);}//如果只是MV的代价就已经大于现有的最小代价就舍弃if (mcost >= min_mcost)   continue;//--- add residual cost to motion cost ---//blocksize_y blocksize_x4 是分块大小16x16 for (y=0; y<blocksize_y; y++) {//(cand_x,cand_y+y)是一行的起始坐标，y++ 遍历每一行ref_line  = get_ref_line (blocksize_x, ref_pic, cand_y+y, cand_x, img_height, img_width);orig_line = orig_pic [y];//计算当前帧和参考帧的像素残差for (x4=0; x4<blocksize_x4; x4++) //以4个为一组计算
      {mcost += byte_abs[ *orig_line++ - *ref_line++ ];mcost += byte_abs[ *orig_line++ - *ref_line++ ];mcost += byte_abs[ *orig_line++ - *ref_line++ ];mcost += byte_abs[ *orig_line++ - *ref_line++ ];}if (mcost >= min_mcost)  //如果已经比最小代价大，就没必要计算下面的行了
      {break;}}//--- check if motion cost is less than minimum cost ---//记录下最小代价和最佳匹配位置if (mcost < min_mcost){best_pos  = pos;min_mcost = mcost;}}//===== set best motion vector and return minimum motion cost =====if (best_pos){*mv_x += spiral_search_x[best_pos];  //因为螺旋搜索数组中记录的是该位置的点*mv_y += spiral_search_y[best_pos];  //与(center_x,center_y)的差
  }return min_mcost;  //返回最小代价
}

//螺旋搜索（全搜索）位置初始化for (k=1, l=1; l<=max(1,search_range); l++){for (i=-l+1; i< l; i++){spiral_search_x[k] =  i;  spiral_search_y[k++] = -l;spiral_search_x[k] =  i;  spiral_search_y[k++] =  l;/**                                 *                         9  3 5 7 10*          1 0 2          11 1 0 2 12*                         13 4 6 8 14* */}for (i=-l;   i<=l; i++){spiral_search_x[k] = -l;  spiral_search_y[k++] =  i;spiral_search_x[k] =  l;  spiral_search_y[k++] =  i;/*                             15 17 19  21 23*         3 5 7                9  3  5  7  10*         1 0 2               11  1  0  2  12*         4 6 8               13  4  6  8  14*                             16 18 20 22  24 */ }}

Fast Full Search

由于运动搜索时有多种块的类型（16x16,8x16,8x8,4x4等）因此，在全搜索时，会由于位置重叠而产生同一处的像素残差多次计算的情况，为了避免这种情况，可以一次性把搜索范围内的所有像素残差计算出来，不同块类型只需要把残差进行组合即可得到该类型的SAD

/*!************************************************************************ brief快速正像素搜索*    Fast Full pixel block motion search*    目标是得到(mv_x,mv_y)和min_mcost，(mv_x,mv_y)指示从哪里开始做分像素搜索，search center*    后者用来跟分像素搜索结果做比较************************************************************************/
int                                                   //  ==> minimum motion cost after search
FastFullPelBlockMotionSearch (pel_t**   orig_pic,     // <--  not usedint       ref,          // <--  reference frame (0... or -1 (backward))int       list,int       pic_pix_x,    // <--  absolute x-coordinate of regarded AxB blockint       pic_pix_y,    // <--  absolute y-coordinate of regarded AxB blockint       blocktype,    // <--  block type (1-16x16 ... 7-4x4)int       pred_mv_x,    // <--  motion vector predictor (x) in sub-pel unitsint       pred_mv_y,    // <--  motion vector predictor (y) in sub-pel unitsint*      mv_x,         //  --> motion vector (x) - in pel unitsint*      mv_y,         //  --> motion vector (y) - in pel unitsint       search_range, // <--  1-d search range in pel unitsint       min_mcost,    // <--  minimum motion cost (cost for center or huge value)double    lambda)       // <--  lagrangian parameter for determining motion cost
{int   pos, offset_x, offset_y, cand_x, cand_y, mcost;int   max_pos       = (2*search_range+1)*(2*search_range+1);              // number of search positionsint   lambda_factor = LAMBDA_FACTOR (lambda);                             // factor for determining lagragian motion costint   best_pos      = 0;                                                  // position with minimum motion costint   block_index;                                                        // block index for indexing SAD arrayint*  block_sad;                                                          // pointer to SAD array
block_index   = (pic_pix_y-img->opix_y)+((pic_pix_x-img->opix_x)>>2); // block index for indexing SAD arrayblock_sad     = BlockSAD[list][ref][blocktype][block_index];         // pointer to SAD array//===== set up fast full integer search if needed / set search center =====if (!search_setup_done[list][ref])//对一个参考帧只做一次
  {//计算搜索范围所有位置所有分块模式的SAD(整像素)SetupFastFullPelSearch (ref, list);}offset_x = search_center_x[list][ref] - img->opix_x; //搜索中心相对原宏块的偏移offset_y = search_center_y[list][ref] - img->opix_y;//===== cost for (0,0)-vector: it is done before, because MVCost can be negative =====//原点(这里的原点都是是当前块所在的位置)if (!input->rdopt){//把刚才计算的SAD 跟mv代价相加得到总代价mcost = block_sad[pos_00[list][ref]] + MV_COST (lambda_factor, 2, 0, 0, pred_mv_x, pred_mv_y);if (mcost < min_mcost){min_mcost = mcost;best_pos  = pos_00[list][ref];//每帧搜索中心的位置
    }}//===== loop over all search positions =====for (pos=0; pos<max_pos; pos++, block_sad++){//--- check residual cost ---if (*block_sad < min_mcost){//--- get motion vector cost ---//计算出搜索位置，按照螺旋形顺序spiral_search_xycand_x = offset_x + spiral_search_x[pos];cand_y = offset_y + spiral_search_y[pos];mcost  = *block_sad;//在SetupFastFullPelSearch已经做好mcost += MV_COST (lambda_factor, 2, cand_x, cand_y, pred_mv_x, pred_mv_y);    //计算 MV 代价//--- check motion cost ---if (mcost < min_mcost){min_mcost = mcost;best_pos  = pos;}}}//===== set best motion vector and return minimum motion cost =====*mv_x = offset_x + spiral_search_x[best_pos];//根据代价最小，计算出最佳MV*mv_y = offset_y + spiral_search_y[best_pos];return min_mcost;
}

Edge Process

通常来说，计算SAD是以一行一行为单位进行，不过在进行搜索时，难免会有运动向量指向图像外的区域，图像以外的这些区域的像素取值为图像边界的值，即

$Pic[x,y]=left{begin{matrix}
Pic[0,y] & x<0\
Pic[width-1,y] & xgeq width\
Pic[x,0] & 0leq x < width,y<0\
Pic[x,height-1] & 0leq x < width,y geq height\
Pic[x,y] & other
end{matrix}right.$

/*如果参考块超出参考帧边界，用边界值进行填充*/
pel_t *UMVLineX (int size, pel_t* Pic, int y, int x, int height, int width)
{int i, maxx;pel_t *Picy;Picy = Pic + max(0,min(height-1,y)) * width;  //先把y范围限制在(0,height-1)内if (x < 0)                            // Left edge
  {maxx = min(0,x+size);   //搜索范围可以大于16的，所以x+16是可以小于0的for (i = x; i < maxx; i++)  //把出界的部分都赋值为边界上的值，一画图就理解了
    {line[i-x] = Picy [0];             // Replicate left edge pixel
    }maxx = x+size;                         //把没出界的像素也拷贝到line数组中    for (i = 0; i < maxx; i++)          // Copy non-edge pixelsline[i-x] = Picy [i];}else if (x > width-size)         // Right edge  同理
  {maxx = width;for (i = x; i < maxx; i++){line[i-x] = Picy [i];             // Copy non-edge pixels
    }maxx = x+size;for (i = max(width,x); i < maxx; i++){line[i-x] = Picy [width-1];  // Replicate right edge pixel
    }}else                                  // No edge  ，则返回y行x列的地址
  {return Picy + x;}return line;    //否则，返回line数组的地址
}