Using wavelet transform (WT) for increasing signal-to-noise ratio (SNR) of discrete-time signals corrupted by additive noise is explained and compared with some other techniques (averaging, frequency filtration, correlation). Signal processing for de-noising is applied to basic periodical signals and repeated transients (in nondestructive ultrasonic testing of welds, where presence of flaws sho...

Abstract In view of the bad operation environment large motor, which often suffers from various strong noise interference, partial discharge ultrasonic signal is annihilated, makes it difficult to detect and analyse. A de-noising method based on generalized minimax concavity (GMC) wavelet for (PD) proposed. GMC used enhance sparsity PD eliminate high-frequency at same time. Then residual sparse...

In this paper the noise suppression with the help of a wavelet transform in synthesis imaging is presented. The method has been used to treat dirty maps observed with the Miyun Synthesis Radio Telescope (MSRT), and the results indicate that the de-noising with the help of the wavelet transform is satisfactory and prospective.

An image is considered as a collection of information stored as intensities and the occurrence of noises. The occurrence of noise present in the image causes degradation in the quality of the image. The basic idea behind image processing is how we estimate the correct pixel values. Image De-noising is one of the fundamental problems which is faced in image processing and computer vision .There ...

There exists a number of cepstral de-noising algorithms which perform quite well when trained and tested under similar acoustic environments, but degrade quickly under mismatched conditions. We present two key results that make these algorithms practical in real noise environments, with the ability to adapt to different acoustic environments over time. First, we show that it is possible to leve...

Magnetic resonance imaging (MRI) is a principal modality of modern medical imaging, which provides a wide spectrum of useful diagnostic contrasts, both anatomical and functional in nature. Like many alternative imaging modalities, however, some specific realizations of MRI offer a trade-off in terms of acquisition time, spatial/temporal resolution and signal-to-noise ratio (SNR). Thus, for inst...

With the growth of the multimedia technology over the past decades, the demand for digital information has increased dramatically. This enormous demand poses difficulties for the current technology to handle. One approach to overcome this problem is to compress the information by removing the redundancies present in it. This is the lossy compression scheme that is often used to compress informa...

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation pr...

Pulsed terahertz (T-ray) imaging systems represent an extremely promising method of obtaining sub-millimetre spectroscopic measurements for a wide range of applications. This paper investigates a number of techniques for optimally processing terahertz data. Speci cally we consider wavelet de-noising andWiener deconvolution algorithms. A goal of this research is the design and implementation of ...

To overcome the shortcomings such as significantly de-noising effect and easily losing the details of the image characteristics of the existing image de-noising methods, an image de-noising algorithm based on the hybrid wavelet transform was proposed. The algorithm integrated the advantages of wavelet de-noising retaining image details features and Wiener filter obtaining the optimal solution, ...