As many traditional de-noising methods fail in the intensive noises environment and are unadaptable in various noisy environments, a method of speech enhancement has been advanced based on dynamic Fractional Fourier Transform (FRFT) filtering. The acoustic signals are framed. The renewing methods are put in FRFT optimal disperse degree of noising speech and this method is implemented in detail....

I introduce a unified approach for de-noising and interpolation of seismic data in the frequency-wavenumber (f-k) domain. First an angular search in the f-k domain is carried out to identify a sparse number of dominant dips, not only using low frequencies but over the whole frequency range. Then, an angular mask function is designed based on the identified dominant dips. The mask function is ut...

The paper puts forward an image de-noising method based on 2D wavelet transform with the application of the method in agricultural data collection system. As the there are influences of various factors in the collection process through wireless image sensor network, the detail signals of each scale are obtained from multi-scale analysis to replace the original signals with smooth low-frequency ...

De-noising algorithms based on wavelet thresholding replace small wavelet coeecients by zero and keep or shrink the coeecients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use Generalized Cross Validation. This procedure does not require an estimate for the noise en...

This paper proposes a spatially adaptive statistical model for wavelet image coefficients in order to perform image de-noising. The wavelet coefficients are modelled as zero-mean Gaussian random variables with high local correlation. This model is developed in a Bayesian framework, where a Maximum Likelihood (ML) estimator evaluates the variance of the blocks to which the wavelet subbands have ...

In this paper, a novel algorithm for PD localization in power transformers based on wavelet de-noising technique and energy criterion is proposed. Partial discharge is one of the main failures in power transformers. The localization of which could be very useful for maintenance systems. Acoustic signals due to a PD event are transient, irregular and non-repetitive. So wavelet transform is an ef...

Original scientific paper Wavelet analysis is a new time-frequency analysis tool developed on the basis of Fourier analysis with good time-frequency localization property and multi-resolution characteristics, which is in a wide range of applications in the field of signal processing. This paper studies the application of wavelet transform in signal filtering, by using an improved particle swarm...

Magnetic resonance imaging (MRI) is extensively exploited for more accurate pathological changes as well as diagnosis. Conversely, MRI suffers from various shortcomings such as ambient noise from the environment, acquisition noise from the equipment, the presence of background tissue, breathing motion, body fat, etc. Consequently, noise reduction is critical as diverse types of the generated no...

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