TITRE Adaptive Packet Video Streaming Over IP Networks - LaBRI

Temporal scalability involves partitioning of the video into layers, where the lower layer is
coded by itself to provide the basic temporal rate and the enhancement layer is coded with
temporal prediction with respect to the lower layer. These layers, when decoded and temporally
multiplexed, yield full temporal resolution. There is also support for temporal scalability by the use
of B pictures. B pictures allow enhancement layer information to be used to increase perceived
quality by increasing the picture rate of the displayed enhanced video sequence. This mode can be
useful for heterogeneous networks with varying bandwidth capacity and also in conjunction with
error correction schemes.
Spatial scalability refers to enhancement information to increase the picture quality by
increasing picture resolution either horizontally, vertically, or both. Spatial scalability involves
generating two spatial resolutions video layers from a single video source such that the lower layer
is coded by itself to provide the basic spatial resolution and the enhancement layer employs the
spatially interpolated lower layer and carries the full spatial resolution of the input video source.
SNR scalability refers to enhancement information to increase the picture quality without
increasing picture resolution. SNR scalability and spatial scalability are equivalent except for the use
of interpolation. Because compression introduces artifacts and distortions, the difference between a
reconstructed picture and its original in the encoder is (nearly always) a nonzero-valued picture,
containing what can be called the coding error. Normally, this coding error is lost at the encoder
and never recovered. With SNR scalability, these coding error pictures can also be encoded and
sent to the decoder, producing an enhancement to the decoded picture. The extra data serves to
increase the signal-to-noise ratio of the video picture, and hence the term SNR scalability.
The Fine Grain Scalability (FGS), often known as the Streaming Profile is intended to support
applications and environment where the bandwidth and/or computational power cannot be
predicted and may vary dynamically. It was developed specially in MPEG-4 in response to the
growing need on a video coding standard for streaming video over the Internet [40]. Three
proposals was submitted to MPEG-4 for achieving FGS, namely, bit-plan coding of the predicted
DCT residue [41][42], wavelet coding of image residue [43][44][45], and matching-pursuit coding of
the predicted DCT residue [46][47]. The bit-plan coding of the predicted DCT residue was finally
accepted after several experiment as a standard for FGS [48].
FGS and its combination with temporal scalability address a variety of challenging problems in
delivering video over the Internet. FGS provides a mechanism that permits a single encoding
process, producing a bitstream that can be modified subsequently in two different ways. Prior to
transmission, the bitstream may be processed to scale it down to known bandwidth limitations.
This can be performed dynamically, for example in response to the requirements of a statistical
multiplexing system. Downstream distribution points may reduce the bit rate if necessary. After the
transmission, the receiver terminal can adapt the received stream to its capabilities.
In [49] [50] [51], another type of FSG was introduced called Progressive Fine Granularity
Scalable coding (PFGS). It improvement over FGS by introducing two prediction loops with
different quality references.
An additional advantage of video scalability is its ability to provide resilience to transmission
errors as the more important data of the lower layer can be sent over a channel with better error
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