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• VP8 Documentation and Test Vector Contributions

  14 octobre 2010, par noreply@blogger.com (John Luther)

  Janne Salonen of the WebM team in Oulu, Finland (formerly On2 Finland) has added a tabular description of the VP8 syntax to the VP8 Bitstream Guide. The new annex provides a concise reference of the elements in the bitstream and we hope will make implementing and testing VP8 decoders easier. The updated document and source can be downloaded from our documentation page.

  We’re working on more improvements to the bitstream guide and invite other community members to help. As with the VP8 code, we gladly give attribution credit to documentation contributors and have added an AUTHORS file to the bitstream-guide Git repository.

  New VP8 Test Vectors

  The Oulu team has also produced some new VP8 test vectors. We analyzed a large set of WebM videos and produced two important corner use cases. The first produces the worst-case memory bandwidth (i.e., lots of global motion, all fractional motion vectors). The second produces the worst-case boolean decoder bin rate over dozens of consecutive frames. These vectors have been added to the VP8 test repository. Our team will consider other corner cases in the next batch of streams we add to the repository.

  Aki Kuusela is Hantro Embedded Engineering Manager at Google.

  

• Tour of Part of the VP8 Process

  18 novembre 2010, par Multimedia Mike — VP8

  My toy VP8 encoder outputs a lot of textual data to illustrate exactly what it’s doing. For those who may not be exactly clear on how this or related algorithms operate, this may prove illuminating.

  Let’s look at subblock 0 of macroblock 0 of a luma plane :

   subblock 0 (original)
    92  91  89  86
    91  90  88  86
    89  89  89  88
    89  87  88  93
  

  Since it’s in the top-left corner of the image to be encoded, the phantom samples above and to the left are implicitly 128 for the purpose of intra prediction (in the VP8 algorithm).

   subblock 0 (original)
       128 128 128 128
   128  92  91  89  86
   128  91  90  88  86
   128  89  89  89  88
   128  89  87  88  93
  

  
  Using the 4×4 DC prediction mode means averaging the 4 top predictors and 4 left predictors. So, the predictor is 128. Subtract this from each element of the subblock :

   subblock 0, predictor removed
   -36 -37 -39 -42
   -37 -38 -40 -42
   -39 -39 -39 -40
   -39 -41 -40 -35
  

  Next, run the subblock through the forward transform :

   subblock 0, transformed
   -312   7   1   0
      1  12  -5   2
      2  -3   3  -1
      1   0  -2   1
  

  Quantize (integer divide) each element ; the DC (first element) and AC (rest of the elements) quantizers are both 4 :

   subblock 0, quantized
   -78   1   0   0
     0   3  -1   0
     0   0   0   0
     0   0   0   0
  

  The above block contains the coefficients that are actually transmitted (zigzagged and entropy-encoded) through the bitstream and decoded on the other end.

  The decoding process looks something like this– after the same coefficients are decoded and rearranged, they are dequantized (multiplied) by the original quantizers :

   subblock 0, dequantized
   -312   4   0   0
      0  12  -4   0
      0   0   0   0
      0   0   0   0
  

  Note that these coefficients are not exactly the same as the original, pre-quantized coefficients. This is a large part of where the “lossy” in “lossy video compression” comes from.

  Next, the decoder generates a base predictor subblock. In this case, it’s all 128 (DC prediction for top-left subblock) :

   subblock 0, predictor
    128 128 128 128
    128 128 128 128
    128 128 128 128
    128 128 128 128
  

  Finally, the dequantized coefficients are shoved through the inverse transform and added to the base predictor block :

   subblock 0, reconstructed
    91  91  89  85
    90  90  89  87
    89  88  89  90
    88  88  89  92
  

  Again, not exactly the same as the original block, but an incredible facsimile thereof.

  Note that this decoding-after-encoding demonstration is not merely pedagogical– the encoder has to decode the subblock because the encoding of successive subblocks may depend on this subblock. The encoder can’t rely on the original representation of the subblock because the decoder won’t have that– it will have the reconstructed block.

  For example, here’s the next subblock :

   subblock 1 (original)
    84  84  87  90
    85  85  86  93
    86  83  83  89
    91  85  84  87
  

  Let’s assume DC prediction once more. The 4 top predictors are still all 128 since this subblock lies along the top row. However, the 4 left predictors are the right edge of the subblock reconstructed in the previous example :

   subblock 1 (original)
      128 128 128 128
   85  84  84  87  90
   87  85  85  86  93
   90  86  83  83  89
   92  91  85  84  87
  

  The DC predictor is computed as (128 + 128 + 128 + 128 + 85 + 87 + 90 + 92 + 4) / 8 = 108 (the extra +4 is for rounding considerations). (Note that in this case, using the original subblock’s right edge would also have resulted in 108, but that’s beside the point.)

  Continuing through the same process as in subblock 0 :

   subblock 1, predictor removed
   -24 -24 -21 -18
   -23 -23 -22 -15
   -22 -25 -25 -19
   -17 -23 -24 -21
   subblock 1, transformed
  
   -173  -9  14  -1
  
      2 -11  -4   0
  
      1   6  -2   3
  
     -5   1   0   1
   subblock 1, quantized
  
   -43  -2   3   0
  
     0  -2  -1   0
  
     0   1   0   0
  
    -1   0   0   0
   subblock 1, dequantized
  
   -172  -8  12   0
  
      0  -8  -4   0
  
      0   4   0   0
  
     -4   0   0   0
   subblock 1, predictor
  
    108 108 108 108
  
    108 108 108 108
  
    108 108 108 108
  
    108 108 108 108
   subblock 1, reconstructed
  
    84  84  87  89
  
    86  85  87  91
  
    86  83  84  89
  
    90  85  84  88
  

  I hope this concrete example (straight from a working codec) clarifies this part of the VP8 process.

• Encoder/Decoder PCM to AMR Android

  2 mars 2013, par Syred

  I've been looking for a while now for any java library that allows me to encode and decode a PCM-AMR audio stream that is sent through a TCP socket connection. Without having to use Android's JNI.

  Is there anything that can help me ?

  In the worst case scenario. How can I do it using any C++ library with JNI ? (any reference of how to use ffmpeg with JNI will be appreciated)

  Hope you can help me.