snow.txt

ffmpeg的完整源代码和作者自己写的文档。不但有在Linux的工程哦

                   ------------                |
                                \        Dequantizaton
 -------------------             \             |
|  Reference frames |             \           IDWT
| -------   ------- |    Motion    \           |
||Frame 0| |Frame 1|| Compensation  .   OBMC   v      -------
| -------   ------- | --------------. \------> + --->|Frame n|-->output
| -------   ------- |                                 -------
||Frame 2| |Frame 3||<----------------------------------/
|        ...        |
 -------------------


Range Coder:
============
FIXME

Neighboring Blocks:
===================
left and top are set to the respective blocks unless they are outside of
the image in which case they are set to the Null block

top-left is set to the top left block unless it is outside of the image in
which case it is set to the left block

if this block has no larger parent block or it is at the left side of its
parent block and the top right block is not outside of the image then the
top right block is used for top-right else the top-left block is used

Null block
y,cb,cr are 128
level, ref, mx and my are 0


Motion Vector Prediction:
=========================
1. the motion vectors of all the neighboring blocks are scaled to
compensate for the difference of reference frames

scaled_mv= (mv * (256 * (current_reference+1) / (mv.reference+1)) + 128)>>8

2. the median of the scaled left, top and top-right vectors is used as
motion vector prediction

3. the used motion vector is the sum of the predictor and
   (mvx_diff, mvy_diff)*mv_scale


Intra DC Predicton:
======================
the luma and chroma values of the left block are used as predictors

the used luma and chroma is the sum of the predictor and y_diff, cb_diff, cr_diff
to reverse this in the decoder apply the following:
block[y][x].dc[0] = block[y][x-1].dc[0] +  y_diff;
block[y][x].dc[1] = block[y][x-1].dc[1] + cb_diff;
block[y][x].dc[2] = block[y][x-1].dc[2] + cr_diff;
block[*][-1].dc[*]= 128;


Motion Compensation:
====================

Halfpel interpolation:
----------------------
halfpel interpolation is done by convolution with the halfpel filter stored
in the header:

horizontal halfpel samples are found by
H1[y][x] =    hcoeff[0]*(F[y][x  ] + F[y][x+1])
            + hcoeff[1]*(F[y][x-1] + F[y][x+2])
            + hcoeff[2]*(F[y][x-2] + F[y][x+3])
            + ...
h1[y][x] = (H1[y][x] + 32)>>6;

vertical halfpel samples are found by
H2[y][x] =    hcoeff[0]*(F[y  ][x] + F[y+1][x])
            + hcoeff[1]*(F[y-1][x] + F[y+2][x])
            + ...
h2[y][x] = (H2[y][x] + 32)>>6;

vertical+horizontal halfpel samples are found by
H3[y][x] =    hcoeff[0]*(H2[y][x  ] + H2[y][x+1])
            + hcoeff[1]*(H2[y][x-1] + H2[y][x+2])
            + ...
H3[y][x] =    hcoeff[0]*(H1[y  ][x] + H1[y+1][x])
            + hcoeff[1]*(H1[y+1][x] + H1[y+2][x])
            + ...
h3[y][x] = (H3[y][x] + 2048)>>12;


                   F   H1  F
                   |   |   |
                   |   |   |
                   |   |   |
                   F   H1  F
                   |   |   |
                   |   |   |
                   |   |   |
   F-------F-------F-> H1<-F-------F-------F
                   v   v   v
                  H2   H3  H2
                   ^   ^   ^
   F-------F-------F-> H1<-F-------F-------F
                   |   |   |
                   |   |   |
                   |   |   |
                   F   H1  F
                   |   |   |
                   |   |   |
                   |   |   |
                   F   H1  F


unavailable fullpel samples (outside the picture for example) shall be equal
to the closest available fullpel sample


Smaller pel interpolation:
--------------------------
if diag_mc is set then points which lie on a line between 2 vertically,
horiziontally or diagonally adjacent halfpel points shall be interpolated
linearls with rounding to nearest and halfway values rounded up.
points which lie on 2 diagonals at the same time should only use the one
diagonal not containing the fullpel point



           F-->O---q---O<--h1->O---q---O<--F
           v \           / v \           / v
           O   O       O   O   O       O   O
           |         /     |     \         |
           q       q       q       q       q
           |     /         |         \     |
           O   O       O   O   O       O   O
           ^ /           \ ^ /           \ ^
          h2-->O---q---O<--h3->O---q---O<--h2
           v \           / v \           / v
           O   O       O   O   O       O   O
           |     \         |         /     |
           q       q       q       q       q
           |         \     |     /         |
           O   O       O   O   O       O   O
           ^ /           \ ^ /           \ ^
           F-->O---q---O<--h1->O---q---O<--F



the remaining points shall be bilinearly interpolated from the
up to 4 surrounding halfpel and fullpel points, again rounding should be to
nearest and halfway values rounded up

compliant snow decoders MUST support 1-1/8 pel luma and 1/2-1/16 pel chroma
interpolation at least


Overlapped block motion compensation:
-------------------------------------
FIXME

LL band prediction:
===================
Each sample in the LL0 subband is predicted by the median of the left, top and
left+top-topleft samples, samples outside the subband shall be considered to
be 0. To reverse this prediction in the decoder apply the following.
for(y=0; y<height; y++){
    for(x=0; x<width; x++){
        sample[y][x] += median(sample[y-1][x],
                               sample[y][x-1],
                               sample[y-1][x]+sample[y][x-1]-sample[y-1][x-1]);
    }
}
sample[-1][*]=sample[*][-1]= 0;
width,height here are the width and height of the LL0 subband not of the final
video


Dequantizaton:
==============
FIXME

Wavelet Transform:
==================

Snow supports 2 wavelet transforms, the symmetric biorthogonal 5/3 integer
transform and a integer approximation of the symmetric biorthogonal 9/7
daubechies wavelet.

2D IDWT (inverse discrete wavelet transform)
--------------------------------------------
The 2D IDWT applies a 2D filter recursively, each time combining the
4 lowest frequency subbands into a single subband until only 1 subband
remains.
The 2D filter is done by first applying a 1D filter in the vertical direction
and then applying it in the horizontal one.
 ---------------    ---------------    ---------------    ---------------
|LL0|HL0|       |  |   |   |       |  |       |       |  |       |       |
|---+---|  HL1  |  | L0|H0 |  HL1  |  |  LL1  |  HL1  |  |       |       |
|LH0|HH0|       |  |   |   |       |  |       |       |  |       |       |
|-------+-------|->|-------+-------|->|-------+-------|->|   L1  |  H1   |->...
|       |       |  |       |       |  |       |       |  |       |       |
|  LH1  |  HH1  |  |  LH1  |  HH1  |  |  LH1  |  HH1  |  |       |       |
|       |       |  |       |       |  |       |       |  |       |       |
 ---------------    ---------------    ---------------    ---------------


1D Filter:
----------
1. interleave the samples of the low and high frequency subbands like
s={L0, H0, L1, H1, L2, H2, L3, H3, ... }
note, this can end with a L or a H, the number of elements shall be w
s[-1] shall be considered equivalent to s[1  ]
s[w ] shall be considered equivalent to s[w-2]

2. perform the lifting steps in order as described below

5/3 Integer filter:
1. s[i] -= (s[i-1] + s[i+1] + 2)>>2; for all even i < w
2. s[i] += (s[i-1] + s[i+1]    )>>1; for all odd  i < w

\ | /|\ | /|\ | /|\ | /|\
 \|/ | \|/ | \|/ | \|/ |
  +  |  +  |  +  |  +  |   -1/4
 /|\ | /|\ | /|\ | /|\ |
/ | \|/ | \|/ | \|/ | \|/
  |  +  |  +  |  +  |  +   +1/2


snows 9/7 Integer filter:
1. s[i] -= (3*(s[i-1] + s[i+1])         + 4)>>3; for all even i < w
2. s[i] -=     s[i-1] + s[i+1]                 ; for all odd  i < w
3. s[i] += (   s[i-1] + s[i+1] + 4*s[i] + 8)>>4; for all even i < w
4. s[i] += (3*(s[i-1] + s[i+1])            )>>1; for all odd  i < w

\ | /|\ | /|\ | /|\ | /|\
 \|/ | \|/ | \|/ | \|/ |
  +  |  +  |  +  |  +  |   -3/8
 /|\ | /|\ | /|\ | /|\ |
/ | \|/ | \|/ | \|/ | \|/
 (|  + (|  + (|  + (|  +   -1
\ + /|\ + /|\ + /|\ + /|\  +1/4
 \|/ | \|/ | \|/ | \|/ |
  +  |  +  |  +  |  +  |   +1/16
 /|\ | /|\ | /|\ | /|\ |
/ | \|/ | \|/ | \|/ | \|/
  |  +  |  +  |  +  |  +   +3/2

optimization tips:
following are exactly identical
(3a)>>1 == a + (a>>1)
(a + 4b + 8)>>4 == ((a>>2) + b + 2)>>2

16bit implementation note:
The IDWT can be implemented with 16bits, but this requires some care to
prevent overflows, the following list, lists the minimum number of bits needed
for some terms
1. lifting step
A= s[i-1] + s[i+1]                              16bit
3*A + 4                                         18bit
A + (A>>1) + 2                                  17bit

3. lifting step
s[i-1] + s[i+1]                                 17bit

4. lifiting step
3*(s[i-1] + s[i+1])                             17bit


TODO:
=====
Important:
finetune initial contexts
flip wavelet?
try to use the wavelet transformed predicted image (motion compensated image) as context for coding the residual coefficients
try the MV length as context for coding the residual coefficients
use extradata for stuff which is in the keyframes now?
the MV median predictor is patented IIRC
implement per picture halfpel interpolation
try different range coder state transition tables for different contexts

Not Important:
compare the 6 tap and 8 tap hpel filters (psnr/bitrate and subjective quality)
spatial_scalability b vs u (!= 0 breaks syntax anyway so we can add a u later)


Credits:
========
Michael Niedermayer
Loren Merritt


Copyright:
==========
GPL + GFDL + whatever is needed to make this a RFC