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The Quality-Affecting Parameters

To generate the distorted video sequences, we used a tool that encodes a real-time video stream over an IP network into H263 format [69], simulates the packetization of the video stream, decodes the received stream and allows us to handle the simulated lost model (See the previous Section). We used a standard video sequence called stefan used to test the performance of H26x and MPEG4 codecs. It contains 300 frames encoded into 30 frames per sec., and lasts 10 sec. The encoded sequence format is CIF (352 lines x 288 pixels). The maximum allowed packet length is 536 bytes, in order to avoid the fragmentation of packets between routers. We present here the quality-affecting parameters that we consider as having the highest impact on quality: The delay and the delay variation are indirectly considered: they are included in the LR parameter. Indeed, it is known that if a dejittering mechanism with adaptive playback buffer size is used, then all the packets arriving after a predefined threshold are considered as lost. So, in this way, all delays and delay variations are mapped into loss. The receiver holds the first packet and some next packets in the buffer for a while before playing them out. There are many studies to find the optimal values of the buffer sizes, the number of packets to be hold in the dejittering buffer and the time at which the first packet in the buffer is to be played out [37]. The amount of the hold time is a measure of the size of the jitter buffer. In article [159], authors argue that the effect of delay and delay jitter can be reduced by the MPEG decoder buffer at the receiver. This is also valid for H263 decoder buffer. A de-jittering scheme for the transport of video over ATM is given in [122]. As stated, the author argues that the scheme can be easily adapted to IP networks. Other study about jitter is given in [162] where it is stated that the jitter affect the decoder buffer size and the loss ratio in a significant way. If we choose to consider all the combinations of these parameters' values, we have to take into account 4x4x5x5x5 = 2000 different combinations. It is the role of the NN to interpolate the quality scores for the missing parts of this potentially large input space. We followed the procedure given in Section 4.3, in page [*], to find the minimum number of combinations to use. Hence, we chose to give default values and to compose different combinations by changing only two parameters at a time. This led to 94 combinations (as shown in Table 6.2). We will see from the next Chapter that this number is sufficient to train and test the NN.
next up previous contents index
Next: Subjective Quality Test and Up: Measuring Video Quality Previous: Network Transport Simulation   Contents   Index
Samir Mohamed 2003-01-08