Discrete-time wavelet transform (DWT) is found to be better than other transforms in the time-varying system analysis, e.g. for time-varying parametric modelling [16], time-varying systems identification [17], time-varying parameter estimation [18] and time domain signal analysis [19]. In the literature the common method to analyze the time-varying system using discrete-time wavelet transform i...

This paper proposes three approaches to content-based watermarking for image authentication based on Independent Component Analysis (ICA). In this scheme, ICA is applied to blocks of the cover image and the resulting mixing matrix is used as the content-based feature. This is embedded in the mid-frequency DCT coefficient of the block in the first method. The watermark is embedded in the 3 rd le...

accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. combined wavelet-artificial neural network (wann) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. this study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...

Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform (DWT) of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; and then invert the DWT to form an estimate of the...

In this paper, we proposed a new artifact level estimation algorithm. The noise model is firstly proposed and 2D discrete wavelet transform is explained. The proposed method is based on Donoho’s approach. From the result section, it is obvious that the proposed method gives favorable results.