Research for the identification method of the image definition based on a W-N model

Abstract

By analyzing the extraction capacity of the image edge feature based on the wavelet transform, and the abilities of the nonlinear processing, the self-adaptive learning and the pattern recognition based on the identification method of the image definition with the neural networks, the identification method of the image definition based on a W-N model is put forward using the human eyes' focusing mechanism based on the neural networks. The wavelet component statistics obtained by the wavelet transform are taken as the inputs of the 5 layer BP neural network model. The model identifies the image definition applying the steepest descent method of the additional momentum in a variable step size to adjust the network weights. The W-N model is first trained by 75 images from a training set, and then is tested by 102 images from a testing set. The results show that it is a very effective identification method which can obtain a higher recognition rate. © 2010 Springer-Verlag Berlin Heidelberg.