mirror of https://git.ffmpeg.org/ffmpeg.git
511 lines
16 KiB
Plaintext
511 lines
16 KiB
Plaintext
=============================================
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SNOW Video Codec Specification Draft 20070103
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=============================================
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Intro:
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======
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This Specification describes the snow syntax and semmantics as well as
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how to decode snow.
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The decoding process is precissely described and any compliant decoder
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MUST produce the exactly same output for a spec conformant snow stream.
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For encoding though any process which generates a stream compliant to
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the syntactical and semmantical requirements and which is decodeable by
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the process described in this spec shall be considered a conformant
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snow encoder.
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Definitions:
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============
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MUST the specific part must be done to conform to this standard
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SHOULD it is recommended to be done that way, but not strictly required
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ilog2(x) is the rounded down logarithm of x with basis 2
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ilog2(0) = 0
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Type definitions:
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=================
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b 1-bit range coded
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u unsigned scalar value range coded
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s signed scalar value range coded
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Bitstream syntax:
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=================
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frame:
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header
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prediction
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residual
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header:
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keyframe b MID_STATE
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if(keyframe || always_reset)
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reset_contexts
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if(keyframe){
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version u header_state
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always_reset b header_state
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temporal_decomposition_type u header_state
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temporal_decomposition_count u header_state
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spatial_decomposition_count u header_state
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colorspace_type u header_state
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chroma_h_shift u header_state
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chroma_v_shift u header_state
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spatial_scalability b header_state
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max_ref_frames-1 u header_state
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qlogs
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}
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if(!keyframe){
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if(!always_reset)
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update_mc b header_state
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if(always_reset || update_mc){
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for(plane=0; plane<2; plane++){
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diag_mc b header_state
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htaps/2-1 u header_state
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for(i= p->htaps/2; i; i--)
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|hcoeff[i]| u header_state
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}
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}
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}
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spatial_decomposition_type s header_state
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qlog s header_state
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mv_scale s header_state
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qbias s header_state
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block_max_depth s header_state
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qlogs:
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for(plane=0; plane<2; plane++){
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quant_table[plane][0][0] s header_state
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for(level=0; level < spatial_decomposition_count; level++){
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quant_table[plane][level][1]s header_state
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quant_table[plane][level][3]s header_state
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}
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}
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reset_contexts
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*_state[*]= MID_STATE
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prediction:
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for(y=0; y<block_count_vertical; y++)
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for(x=0; x<block_count_horizontal; x++)
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block(0)
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block(level):
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if(keyframe){
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intra=1
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y_diff=cb_diff=cr_diff=0
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}else{
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if(level!=max_block_depth){
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s_context= 2*left->level + 2*top->level + topleft->level + topright->level
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leaf b block_state[4 + s_context]
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}
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if(level==max_block_depth || leaf){
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intra b block_state[1 + left->intra + top->intra]
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if(intra){
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y_diff s block_state[32]
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cb_diff s block_state[64]
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cr_diff s block_state[96]
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}else{
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ref_context= ilog2(2*left->ref) + ilog2(2*top->ref)
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if(ref_frames > 1)
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ref u block_state[128 + 1024 + 32*ref_context]
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mx_context= ilog2(2*abs(left->mx - top->mx))
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my_context= ilog2(2*abs(left->my - top->my))
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mvx_diff s block_state[128 + 32*(mx_context + 16*!!ref)]
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mvy_diff s block_state[128 + 32*(my_context + 16*!!ref)]
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}
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}else{
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block(level+1)
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block(level+1)
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block(level+1)
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block(level+1)
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}
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}
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residual:
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FIXME
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Tag description:
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----------------
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version
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0
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this MUST NOT change within a bitstream
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always_reset
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if 1 then the range coder contexts will be reset after each frame
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temporal_decomposition_type
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0
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temporal_decomposition_count
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0
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spatial_decomposition_count
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FIXME
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colorspace_type
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0
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this MUST NOT change within a bitstream
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chroma_h_shift
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log2(luma.width / chroma.width)
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this MUST NOT change within a bitstream
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chroma_v_shift
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log2(luma.height / chroma.height)
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this MUST NOT change within a bitstream
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spatial_scalability
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0
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max_ref_frames
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maximum number of reference frames
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this MUST NOT change within a bitstream
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update_mc
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indicates that motion compensation filter parameters are stored in the
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header
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diag_mc
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flag to enable faster diagonal interpolation
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this SHOULD be 1 unless it turns out to be covered by a valid patent
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htaps
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number of half pel interpolation filter taps, MUST be even, >0 and <10
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hcoeff
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half pel interpolation filter coefficients, hcoeff[0] are the 2 middle
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coefficients [1] are the next outer ones and so on, resulting in a filter
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like: ...eff[2], hcoeff[1], hcoeff[0], hcoeff[0], hcoeff[1], hcoeff[2] ...
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the sign of the coefficients is not explicitly stored but alternates
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after each coeff and coeff[0] is positive, so ...,+,-,+,-,+,+,-,+,-,+,...
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hcoeff[0] is not explicitly stored but found by subtracting the sum
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of all stored coefficients with signs from 32
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hcoeff[0]= 32 - hcoeff[1] - hcoeff[2] - ...
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a good choice for hcoeff and htaps is
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htaps= 6
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hcoeff={40,-10,2}
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an alternative which requires more computations at both encoder and
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decoder side and may or may not be better is
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htaps= 8
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hcoeff={42,-14,6,-2}
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ref_frames
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minimum of the number of available reference frames and max_ref_frames
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for example the first frame after a key frame always has ref_frames=1
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spatial_decomposition_type
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wavelet type
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0 is a 9/7 symmetric compact integer wavelet
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1 is a 5/3 symmetric compact integer wavelet
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others are reserved
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stored as delta from last, last is reset to 0 if always_reset || keyframe
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qlog
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quality (logarthmic quantizer scale)
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stored as delta from last, last is reset to 0 if always_reset || keyframe
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mv_scale
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stored as delta from last, last is reset to 0 if always_reset || keyframe
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FIXME check that everything works fine if this changes between frames
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qbias
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dequantization bias
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stored as delta from last, last is reset to 0 if always_reset || keyframe
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block_max_depth
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maximum depth of the block tree
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stored as delta from last, last is reset to 0 if always_reset || keyframe
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quant_table
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quantiztation table
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Range Coder:
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============
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FIXME
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Neighboring Blocks:
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===================
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left and top are set to the respective blocks unless they are outside of
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the image in which case they are set to the Null block
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top-left is set to the top left block unless it is outside of the image in
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which case it is set to the left block
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if this block has no larger parent block or it is at the left side of its
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parent block and the top right block is not outside of the image then the
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top right block is used for top-right else the top-left block is used
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Null block
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y,cb,cr are 128
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level, ref, mx and my are 0
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Motion Vector Prediction:
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=========================
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1. the motion vectors of all the neighboring blocks are scaled to
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compensate for the difference of reference frames
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scaled_mv= (mv * (256 * (current_reference+1) / (mv.reference+1)) + 128)>>8
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2. the median of the scaled left, top and top-right vectors is used as
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motion vector prediction
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3. the used motion vector is the sum of the predictor and
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(mvx_diff, mvy_diff)*mv_scale
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Intra DC Predicton:
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======================
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the luma and chroma values of the left block are used as predictors
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the used luma and chroma is the sum of the predictor and y_diff, cb_diff, cr_diff
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to reverse this in the decoder apply the following:
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block[y][x].dc[0] += block[y][x-1].dc[0];
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block[y][x].dc[1] += block[y][x-1].dc[1];
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block[y][x].dc[2] += block[y][x-1].dc[2];
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block[*][-1].dc[*]= 128;
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Motion Compensation:
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====================
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Halfpel interpolation:
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----------------------
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halfpel interpolation is done by convolution with the halfpel filter stored
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in the header:
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horizontal halfpel samples are found by
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H1[y][x] = hcoeff[0]*(F[y][x ] + F[y][x+1])
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+ hcoeff[1]*(F[y][x-1] + F[y][x+2])
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+ hcoeff[2]*(F[y][x-2] + F[y][x+3])
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+ ...
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h1[y][x] = (H1[y][x] + 32)>>6;
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vertical halfpel samples are found by
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H2[y][x] = hcoeff[0]*(F[y ][x] + F[y+1][x])
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+ hcoeff[1]*(F[y-1][x] + F[y+2][x])
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+ ...
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h2[y][x] = (H2[y][x] + 32)>>6;
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vertical+horizontal halfpel samples are found by
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H3[y][x] = hcoeff[0]*(H2[y][x ] + H2[y][x+1])
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+ hcoeff[1]*(H2[y][x-1] + H2[y][x+2])
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+ ...
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H3[y][x] = hcoeff[0]*(H1[y ][x] + H1[y+1][x])
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+ hcoeff[1]*(H1[y+1][x] + H1[y+2][x])
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+ ...
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h3[y][x] = (H3[y][x] + 2048)>>12;
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F H1 F
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F H1 F
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F-------F-------F-> H1<-F-------F-------F
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v v v
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H2 H3 H2
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^ ^ ^
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F-------F-------F-> H1<-F-------F-------F
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F H1 F
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F H1 F
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unavailable fullpel samples (outside the picture for example) shall be equal
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to the closest available fullpel sample
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Smaller pel interpolation:
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--------------------------
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if diag_mc is set then points which lie on a line between 2 vertically,
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horiziontally or diagonally adjacent halfpel points shall be interpolated
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linearls with rounding to nearest and halfway values rounded up.
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points which lie on 2 diagonals at the same time should only use the one
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diagonal not containing the fullpel point
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F-->O---q---O<--h1->O---q---O<--F
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v \ / v \ / v
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O O O O O O O
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| / | \ |
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q q q q q
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| / | \ |
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O O O O O O O
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^ / \ ^ / \ ^
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h2-->O---q---O<--h3->O---q---O<--h2
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v \ / v \ / v
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O O O O O O O
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| \ | / |
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q q q q q
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O O O O O O O
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^ / \ ^ / \ ^
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F-->O---q---O<--h1->O---q---O<--F
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the remaining points shall be bilinearly interpolated from the
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up to 4 surrounding halfpel points, again rounding should be to nearest and
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halfway values rounded up
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compliant snow decoders MUST support 1-1/8 pel luma and 1/2-1/16 pel chroma
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interpolation at least
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Overlapped block motion compensation:
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-------------------------------------
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FIXME
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LL band prediction:
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===================
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Each sample in the LL0 subband is predicted by the median of the left, top and
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left+top-topleft samples, samples outside the subband shall be considered to
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be 0. To reverse this prediction in the decoder apply the following.
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for(y=0; y<height; y++){
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for(x=0; x<width; x++){
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sample[y][x] += median(sample[y-1][x],
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sample[y][x-1],
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sample[y-1][x]+sample[y][x-1]-sample[y-1][x-1]);
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}
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}
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sample[-1][*]=sample[*][-1]= 0;
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width,height here are the width and height of the LL0 subband not of the final
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video
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Dequantizaton:
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==============
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FIXME
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Wavelet Transform:
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==================
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Snow supports 2 wavelet transforms, the symmetric biorthogonal 5/3 integer
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transform and a integer approximation of the symmetric biorthogonal 9/7
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daubechies wavelet.
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2D IDWT (inverse discrete wavelet transform)
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--------------------------------------------
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The 2D IDWT applies a 2D filter recursively, each time combining the
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4 lowest frequency subbands into a single subband until only 1 subband
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remains.
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The 2D filter is done by first applying a 1D filter in the vertical direction
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and then applying it in the horizontal one.
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--------------- --------------- --------------- ---------------
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|LL0|HL0| | | | | | | | | | | |
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|---+---| HL1 | | L0|H0 | HL1 | | LL1 | HL1 | | | |
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|LH0|HH0| | | | | | | | | | | |
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|-------+-------|->|-------+-------|->|-------+-------|->| L1 | H1 |->...
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| LH1 | HH1 | | LH1 | HH1 | | LH1 | HH1 | | | |
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--------------- --------------- --------------- ---------------
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1D Filter:
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----------
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1. interleave the samples of the low and high frequency subbands like
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s={L0, H0, L1, H1, L2, H2, L3, H3, ... }
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note, this can end with a L or a H, the number of elements shall be w
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s[-1] shall be considered equivalent to s[1 ]
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s[w ] shall be considered equivalent to s[w-2]
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2. perform the lifting steps in order as described below
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5/3 Integer filter:
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1. s[i] -= (s[i-1] + s[i+1] + 2)>>2; for all even i < w
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2. s[i] += (s[i-1] + s[i+1] )>>1; for all odd i < w
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\ | /|\ | /|\ | /|\ | /|\
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\|/ | \|/ | \|/ | \|/ |
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+ | + | + | + | -1/4
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/|\ | /|\ | /|\ | /|\ |
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/ | \|/ | \|/ | \|/ | \|/
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| + | + | + | + +1/2
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snows 9/7 Integer filter:
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1. s[i] -= (3*(s[i-1] + s[i+1]) + 4)>>3; for all even i < w
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2. s[i] -= s[i-1] + s[i+1] ; for all odd i < w
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3. s[i] += ( s[i-1] + s[i+1] + 4*s[i] + 8)>>4; for all even i < w
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4. s[i] += (3*(s[i-1] + s[i+1]) )>>1; for all odd i < w
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\ | /|\ | /|\ | /|\ | /|\
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\|/ | \|/ | \|/ | \|/ |
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+ | + | + | + | -3/8
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/|\ | /|\ | /|\ | /|\ |
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/ | \|/ | \|/ | \|/ | \|/
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(| + (| + (| + (| + -1
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\ + /|\ + /|\ + /|\ + /|\ +1/4
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\|/ | \|/ | \|/ | \|/ |
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+ | + | + | + | +1/16
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/|\ | /|\ | /|\ | /|\ |
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/ | \|/ | \|/ | \|/ | \|/
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| + | + | + | + +3/2
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optimization tips:
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following are exactly identical
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(3a)>>1 == a + (a>>1)
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(a + 4b + 8)>>4 == ((a>>2) + b + 2)>>2
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16bit implementation note:
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The IDWT can be implemented with 16bits, but this requires some care to
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prevent overflows, the following list, lists the minimum number of bits needed
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for some terms
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1. lifting step
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A= s[i-1] + s[i+1] 16bit
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3*A + 4 18bit
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A + (A>>1) + 2 17bit
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3. lifting step
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s[i-1] + s[i+1] 17bit
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4. lifiting step
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3*(s[i-1] + s[i+1]) 17bit
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TODO:
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=====
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Important:
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finetune initial contexts
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spatial_decomposition_count per frame?
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flip wavelet?
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try to use the wavelet transformed predicted image (motion compensated image) as context for coding the residual coefficients
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try the MV length as context for coding the residual coefficients
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use extradata for stuff which is in the keyframes now?
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the MV median predictor is patented IIRC
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change MC so per picture halfpel interpolation can be done and finish the implementation of it
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compare the 6 tap and 8 tap hpel filters (psnr/bitrate and subjective quality)
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try different range coder state transition tables for different contexts
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Not Important:
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spatial_scalability b vs u (!= 0 breaks syntax anyway so we can add a u later)
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Credits:
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========
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Michael Niedermayer
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Loren Merritt
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Copyright:
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==========
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GPL + GFDL + whatever is needed to make this a RFC
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