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A methods using stationary wavelet transform based on multi-scales total least squares for image denoising is proposed.The noisy image is decomposited using stationary wavelet.For the high frequency components of image decomposition,the wavelet coefficients are estimated using total least squares.The interscale correlations of wavelet coefficients are considered.The multi-scales total least squares for estimating wavelet coefficients is proposed.Then the high frequency coefficients of signal are obtained.The denoised image is obtained through inverse wavelet transform.The experimental results show that the image can be denoised effectively based on total least squares using the interscale correlations of wavelet coefficients.The SNR and the visual quality are improved substantially.

Ions bombardment is very important in thin films and surface processing. The ion energy and ion flux are two important parameters in ion bombardment. The ion current density mainly dependent on the plasma density gives the number of energetic ions bombarding the substrate. The self-bias voltage in plasma sheath accelerates plasma ions towards the substrate. RF discharge can increase plasma density and RF bias can also provide the insulator substrate with a plasma sheath. In order to choose and control ion energy, ion density, the angle of incidence, and ion species, ion beam sources are used. New types of electrodeless ion sources (RF, MW, ECR-MW) have been introduced in detail. In the last, the effects of ion bombardment on thin films and surface processing are presented.

An inductively coupled radio frequency ion source has been developed and its extraction characteristics measured. Beam current density up to 0.11 mA/ cm2 was obtained with argon at a rf discharge power of about 140 W. The dependences of ion beam on the discharge parameters such as rf source power, gas pressure and gas flow rate was studied.

The problems of signal detection and parameter estimation are of fundamental importance in detection and recognition of weak target. The typical problem is the measurement of the harmonic signal parameter in the noise. In traditional theory, the processing method is based on uniformly sampling and all the data have the same effect. This paper presents a novel theory to deal with the problem, which treats the data in a different way. The novel method is based on the sub-sampling technique. The position of the new sampling data is not regular in source sequence, but they have the same feature that they are affected by noise less seriously than those that are deserted. Since the new data is not uniformly sampled, the traditional estimation algorithm will be modified and a novel algorithm is discussed to deal with the sub-sampling data. The method presented in the paper offer the higher accuracy of the estimation, because the sub-sampling data have higher SNR. Computer simulations are used to obtain the parameter estimation performance results. Results obtained by this new method are compared with traditional FFT method, and the parameters obtained by new method are more accurate