Name
Abstract | ||
|---|---|---|
An adaptive quantization algorithm for MPEG-2 video coding using a neural network is presented in this paper. The proposed algorithm uses a backpropagation neural network to divide the macroblock activity into one of four categories: flat, edge, texture, fine-texture, and thus the macroblock can be quantized adaptively according to the human vision system (HVS) sensitivity. Experimental results show that this method can reduce block artifacts of flat area and distortion at edge effectively. Meanwhile, the picture subjective quality and objective quality of each frame are improved |
Year | DOI | Venue |
|---|---|---|
1998 | null | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Keywords | Field | DocType |
null | Computer science,Artificial intelligence,Artificial neural network,Distortion,MPEG-2,Macroblock,Computer vision,Coding tree unit,Pattern recognition,Image texture,Algorithm,Backpropagation,Quantization (signal processing) | Conference |
Volume | Issue | ISSN |
5 | null | null |
ISBN | Citations | PageRank |
0-7803-4428-6 | 1 | 0.46 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li-Jun Luo | 1 | 18 | 2.89 |
| Cairong Zou | 2 | 415 | 27.19 |
| Zhenya He | 3 | 207 | 38.98 |
| Isao Shirakawa | 4 | 1 | 0.46 |