Using Mean Squared error instead of SAD for image compensation - c++

Question

I have an assignment where image composition is done using SAD. And another task is to use MSE instead of SAD in the code. Im struggling with it so can anyone help me with this? Here is the code for SAD.
find_motion(my_image_comp *ref, my_image_comp *tgt,
int start_row, int start_col, int block_width, int block_height)
/* This function finds the motion vector which best describes the motion
between the `ref' and `tgt' frames, over a specified block in the
`tgt' frame. Specifically, the block in the `tgt' frame commences
at the coordinates given by `start_row' and `start_col' and extends
over `block_width' columns and `block_height' rows. The function finds
the translational offset (the returned vector) which describes the
best matching block of the same size in the `ref' frame, where
the "best match" is interpreted as the one which minimizes the sum of
absolute differences (SAD) metric. */
{
mvector vec, best_vec;
int sad, best_sad=256*block_width*block_height;
for (vec.y=-8; vec.y <= 8; vec.y++)
for (vec.x=-8; vec.x <= 8; vec.x++)
{
int ref_row = start_row-vec.y;
int ref_col = start_col-vec.x;
if ((ref_row < 0) || (ref_col < 0) ||
((ref_row+block_height) > ref->height) ||
((ref_col+block_width) > ref->width))
continue; // Translated block not containe within reference frame
int r, c;
int *rp = ref->buf + ref_row*ref->stride + ref_col;
int *tp = tgt->buf + start_row*tgt->stride + start_col;
for (sad=0, r=block_height; r > 0; r--,
rp+=ref->stride, tp+=tgt->stride)
for (c=0; c < block_width; c++)
{
int diff = tp[c] - rp[c];
sad += (diff < 0)?(-diff):diff;
}
if (sad < best_sad)
{
best_sad = sad;
best_vec = vec;
}
}
return best_vec;
}

Answer 1

I got the answer myself I think.
its,
for (mse = 0, r = block_height; r > 0; r--,
rp+=ref->stride, tp+=tgt->stride)
for (c=0; c < block_width; c++)
{
int diff = tp[c] - rp[c];
temp = (diff*diff) / (block_height*block_width);
mse += temp;
temp = 0;
}
if (mse < best_mse)
{
best_mse = mse;
best_vec = vec;
}
}
return best_vec;
}