Probabilistic PCA self-organizing maps
IEEE Transactions on Neural Networks
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Only a limited number of methods have been proposed to realize heterogeneous transcoding, for example from MPEG-2 to H.263, or from H.264 to H.263. The major difficulties of transcoding a B-picture to a P-picture are that the incoming discrete cosine transform (DCT) coefficients of the B-frame are prediction errors arising from both forward and backward predictions, whilst the prediction errors in the DCT domain arising from the prediction using the previous frame alone are not available. The required new prediction errors need to be re-estimated in the pixel domain. This process involves highly complex computation and introduces re-encoding errors. We propose a new approach to convert a B-picture into a P-picture by making use of some properties of motion compensation in the DCT domain and the direct addition of DCT coefficients. We derive a set of equations and formulate the problem of how to obtain the DCT coefficients. One difficulty is that the last P-frame inside a GOP with an IBBP structure, for example, needs to be transcoded to become the last P-frame in the IPPP structure, and it has to be linked to the previous reconstructed P-frame instead of to the I-frame. We increased the speed of the transcoding process by making use of the motion activity which is expressed in terms of the correlation between pictures. The whole transcoding process is done in the transform domain, hence re-encoding errors are completely avoided. Results from our experimental work show that the proposed video transcoder not only achieves a speed-up of two to six times that of the conventional video transcoder, but it also substantially improves the quality of the video.