REDES NEURONALES ARTIFICIALES APLICADAS AL PROCESAMIENTO DE VIDEO.

The motion estimation is an essential block in the prediction stage of the H.264/AVC video compression standard, which is crucial for obtaining an effective coding rate. Different algorithms have been proposed in the literature to optimize the architecture of this block, since it requires a long execution time and a significant number of computational resources. Traditional strategies based on the search on each block allow ensuring high quality but are inappropriate in terms of computational efficiency; other methods based on search by regions reduce the processing load, but do not guarantee a good quality. In this paper it is implemented a multilayer perceptron neural network with supervised backpropagation learning algorithm which allows making the estimation. [ABSTRACT FROM AUTHOR]