THE RECOGNITION OF THREE-CHANNEL WAVELET FILTER BANKS BASED ON CNN AND FUSION TARGET
In order to solve the problem of manual selection of two-dimensional non-separable wavelet filter for image fusion,this paper proposes an automatic selection and classification method for of three-channel non-separable symmetric wavelet filter banks based on CNN and fusion image definition.Lots of well-distributed 3×5symmetrical wavelet filter banks were constructed.The multi-focus images were fused by using these filter banks.And the labels of fusion definition were set according to the fusion results along with constructing the training set and testing set.A classified convolutional neural network was designed,and a new network model was acquired after training.Filter banks outside the training set and the testing set were recognized and analyzed.The experiment results show that the recognition rate of the network model to the data set that is inside or outside the testing set is 99.48％and 99.58％respectively,both of which have higher recognition rate,and the better class of the filter banks has higher definition for multi-focus image fu-sion.
万方数据
维普
