From the view points of media editing, it is desired that pictures in an video sequence could be coded in picture-by-picture sense. But, in order to increase the compression ratio, the temporal correlation among pictu...
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From the view points of media editing, it is desired that pictures in an video sequence could be coded in picture-by-picture sense. But, in order to increase the compression ratio, the temporal correlation among pictures must be taken into account. Instead of using JPEG or MPEG alone, in this paper, a transform-domain transcoding approach is proposed to achieve the above goal. Based on the proposed transcoding algorithm, a low-cost and low-bit-rate editing system, which produces MPEG-1 decodable bitstreams, has been constructed.
Formerly, once the audio data is compressed, transcoding is used to scale the bit rate, where decoding and re-encoding are taking place. Therefore, data manipulation of coded data has been very complex and time consum...
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Formerly, once the audio data is compressed, transcoding is used to scale the bit rate, where decoding and re-encoding are taking place. Therefore, data manipulation of coded data has been very complex and time consuming work. We describe three algorithms for bit rate scaling in the coded MPEG data domain. One is a bandwidth limitation method cutting higher frequency components until the target data rate is satisfied. The other two use a re-quantization process where a quantization step in each subband is modified. One of them reflects the psychoacoustic model from bit allocation information obtained in the bitstream in order to improve the bit rate scaling efficiency. The simulation results show that the re-quantization process provides a very high conversion efficiency and a nearly equal sound quality can be obtained as directly coding from PCM by reflecting the psychoacoustic model. It is also shown that a very fast scaling (factor of six) have been achieved when compared with the transcoding method.
Compressed digital video is becoming prevalent for video storage and communication. It is often desirable to perform various video processing tasks on compressed video streams, however, operations once considered simp...
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Compressed digital video is becoming prevalent for video storage and communication. It is often desirable to perform various video processing tasks on compressed video streams, however, operations once considered simple, such as splicing and reverse play, are much more complex in the context of compressed video. The conceptually-simple approach of completely decoding the video into the pixel domain, performing the processing, and re-encoding the entire video sequence is often inefficient and impractical. This paper investigates the problem of transcoding compressed video data from one standards-compliant data stream to another. The goal is to develop video transcoding algorithms that achieve high performance with computational efficiency. In particular, this paper presents efficient algorithms for splicing and reverse play of compressed video streams.
Two different models for transcoding of H.263-based video streams are examined: rate reduction and resolution reduction. Results show that the computational complexity of the basic transcoding model can be reduced for...
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Two different models for transcoding of H.263-based video streams are examined: rate reduction and resolution reduction. Results show that the computational complexity of the basic transcoding model can be reduced for each model by an average of 39% and 23% with less than 1 dB loss in quality for sequences with high motion. Comparisons with scalable video coding model are also presented.
In this paper we address the problem of video internetworking where a compressed bit stream is transmitted through networks of different capacities. Using a video transcoding architecture previously proposed by the au...
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In this paper we address the problem of video internetworking where a compressed bit stream is transmitted through networks of different capacities. Using a video transcoding architecture previously proposed by the authors, an efficient bit rate control algorithm is devised in order to match the bit rate ratio to a given network bandwidth constraint. By using a dynamic control of the transcoding buffer, different compression ratios are achieved for each type of picture in MPEG-2 coded video. It is shown that transcoded picture quality is almost the same as that obtained by directly encoding the uncompressed video at the same lower rates. The proposed algorithm has low latency and is computationally very simple.
This paper is concerned with the performance of MPEG-II compressed video when transmitted over noisy channels, such as for digital terrestrial television. We present the results of bit sensitivity and resynchronisatio...
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This paper is concerned with the performance of MPEG-II compressed video when transmitted over noisy channels, such as for digital terrestrial television. We present the results of bit sensitivity and resynchronisation sensitivity measurements, and propose techniques for substantially improving the resilience of MPEG-II to transmission errors without increasing the bit rate.
As the number of different video compression algorithms in use and also the specific bit rates at which they are operated increase, there is a growing need for converters from one algorithm or bit rate to another. In ...
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As the number of different video compression algorithms in use and also the specific bit rates at which they are operated increase, there is a growing need for converters from one algorithm or bit rate to another. In general, this can only be accomplished by decoding and re-encoding. It has previously been assumed that the additional delays introduced by such decoding and re-encoding are additive and thereby become unacceptable for some interactive applications. This paper shows that it is possible to construct a transcoder such that the aggregate end-to-end delay is substantially less than the sum of the delays from the two encode and decode pairs. Two techniques are described. The first is more general while the second is simpler but is restricted to the case of reducing the bit rate and keeping: the same compression algorithm. Results from simulations of the latter method are included.
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