Title :
A neural network based transcoder for MPEG2 video compression
Author :
Fu, H.C. ; Chen, ZH ; Xu, Y.Y. ; Wang, C.H.
Author_Institution :
Dept. of Comput. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
We propose a neural network method for the high efficiency requatization in the design of a transcoder. In our design, there are two types of video bit rate control in the proposed transcoder. One is the global adjustment of the quantizer scales in which the adjustment is based on the complication of the whole frame, the other is the adaptive adjustment of the quantizer scales, where the adjustment results in a complication of the current macroblock. From the experimental results, the prototype transcoder can achieve a desirable bit rate (1.5 Mbps) with an acceptable image quality. In addition, we constructed a video multiplexer for pay per view (PPV) or near video on demand (NVOD) applications on the proposed transcoder
Keywords :
code standards; data compression; multilayer perceptrons; multiplexing equipment; quantisation (signal); telecommunication standards; video coding; video on demand; MPEG2 video compression; NVOD; adaptive adjustment; experimental results; global adjustment; high efficiency requatization; image quality; macroblock; multilayer perceptron; near video on demand; neural network based transcoder; pay per view; prototype transcoder; quantizer scales; transcoder design; video bit rate control; video multiplexer; Bit rate; Decoding; Image coding; Image quality; Neural networks; Quantization; Streaming media; TV; Transform coding; Video compression;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.759942
