Identification of blur parameters from motion blurred images
Graphical Models and Image Processing
Digital Image Restoration
IEEE Transactions on Information Theory
A spatially adaptive nonparametric regression image deblurring
IEEE Transactions on Image Processing
An optimal robust digital image watermarking based on genetic algorithms in multiwavelet domain
WSEAS Transactions on Signal Processing
A robust watermarking technique for copyright protection using discrete wavelet transform
WSEAS Transactions on Computers
Robust audio watermarking using multiwavelet transform and genetic algorithm
WSEAS TRANSACTIONS on SYSTEMS
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This paper proposes a new blind watermarking scheme based on discrete wavelet transform(DWT) domain. The method uses the HVS model, and radial basis function neural networks(RBF). RBF will be implemented while embedding and extracting watermark. The human visual system (HVS) model is used to determine the watermark insertion strength. The neural networks almost exactly recover the watermarking signals from the watermarked images after training and learning. The experimental results show that the watermark proposed in this paper is invisible (the PSNR is higher than 41) and is robust in the case of against some normal at tacks such as JPEG compression, additive noise and filtering, etc.