Image de-noising and clustering in medical images are quite complex because of narrow dynamic range and in-homogeneity. Pre processing steps like image de-noising do have influence over the subsequent image processing which misleads further image analysis. In this paper, a new method which incorporates the advantages of adaptive center weighted median filter and hybrid median filter, called Ite...

In many image transmission and acquisition situations, the image may become cornlpted by additive noise. De-noising refers to the process of removing the noise while maintaining good visual quality. This problem has assumed major significance with the increase in image related communication that has accompanied the exponential growth of the intemet. Traditionally, image quality is measured in t...

Gearbox is an important mechanical device to transmit power. In order to ensure the normal operation of gearbox under the condition of top load, high efficiency and high precision, it’s necessary to extract fault feature information using signal processing method and to further analyze and research gearbox fault. In the paper an improved de-noising method based on de-noising of singular value d...

A new approach to modified S-transform based non-stationary power signal de-noising is presented in this paper. Modified S-transform is employed in de-noising techniques to separate high frequency noise which is prevalent in practical signals like power disturbance signals from the low frequency undistorted signals. In this we have tried to bring out the advantage of the modified S-transform an...

Introduction: SPECT is a diagnostic imaging technique the main disadvantage of which is the existence of Poisson noise. So far, different methods have been used by scientists to improve SPECT images. The Wavelet Transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. The purpose of this paper is evaluation of noise reduction in SPECT ...

This paper proposes time-frequency analysis of EEG spectrum and wavelet analysis in EEG de-noising. In this paper, the basic idea is to use the characteristics of multi-scale multi-resolution, using four different thresholds to wipe off interference and noise after decomposition of the EEG signals. By analyzing the results, understanding the effects of four different methods, it comes to a conc...

As to the hybrid noise characteristic, a mixed de-noising method is hereby proposed in combination with the median filter and the wavelet transform. Firstly, conduct the median filter to the pending image; then apply an improved threshold function to the wavelet transform (WT) to eliminate noise; finally, adopt Signal Noise Ratio (SNR) to evaluate the image de-noising effect. The experiment res...

The s-transform is a variable window of STFT and extension of wavelet. This paper discussed the principle and method of Wavelet De-noising, reduced noise of pulse signal based on wavelet. It is shown that wavelet de-noising can eliminate most noise, and preserve effectively sudden change of signal. This paper analyzed and compared the effect of denoising of pulse signal in different ways all st...

There are various de-noising algorithms and optimization methods for different signal and noise characteristics. However, the signals used in real application may have deviations from the model. For example: signal and/or noise may not be stationary or a proper model for them may not be available. MCG (magnetocardiography) is an example signal, where conventional de-noising methods are not givi...

The purpose of the ct-image de-noising is an important research topic both in image processing and biomedical engineering. Independent component analysis (ica) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. The curve let transform as a multiscale transform has directional parameters...