Motion search region prediction using neural network vector quantization
Dong Hee Ryu, C.R. Kim, S.W. Kim, Taewon Choi, J.C. Kim · 2002
This paper presents a new search region prediction method using the neural networks vector quantization (VQ) in the motion estimation. A major advantage of formulating VQ as neural networks is that the large number of adaptive training algorithm that are used for neural networks can be applied to VQ. The proposed method reduces the computation because of the smaller number of search points than conventional methods, and reduces the bits required to represent motion vectors. The results of computer simulation show that the proposed method provides better PSNR than other block matching algorithms.