Search Region Prediction for Motion Estimation Based on Neural Network Vector Quantization

We present a new search region prediction method using frequency sensitive competitive learning vector quantization for motion estimation of image sequences. The proposed method can decrease the computation time because of the smaller number of search points compared to other methods, and also reduces the bits required to represent motion vectors. The results of experiments show that the proposed method provides competitive PSNR values compared to other block matching algorithms while reducing the number of search points and minimizing the complexity of the search region prediction process.