The de-noising is a challenging task in the field of signal and image processing. Any natural image corrupted by gussian noise can be de-noised using wavelet method. Wavelet-based image denoising is an important technique in the area of image noise reduction. Wavelets have their natural ability to represent images in a very sparse form which is the foundation of wavelet-based denoising through ...

An analog QRS complex detection circuit, for pacemaker applications, based on the Wavelet Transform (WT) is presented. The system detects the wavelet modulus maxima of the QRS complex. It consists of a wavelet transform filter, an absolute value circuit, a peak detector and a comparator. In order to achieve the low-power requirement in pacemakers, we propose a new method for implementing the WT...

this paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. jpeg2000 standard is a common standard that uses discrete wavelet transform (dwt) in the compression process. the main problems of dwt are failure to detect curved edges in image and its shortage representation of the ridge and furrow patterns which cause deficiency and block artifacts rema...

For signal processing, the Wavelet transform (WT) has been shown to be a very promising mathematical tool. WT is efficient for local analysis of nonstationary and fast transient signals due its good estimation of time and frequency localization. In the complex wavelet transform analysis, the modulus maxima and the ± π/2 phase crossings point out the locations of sharp signal transitions. The ph...

Although most of its popular applications have been in discrete-time signal processing for over two decades, wavelet transform theory offers a methodology to generate continuoustime compact support orthogonal filter banks through the design of discrete-time finite length filter banks with multiple time and frequency resolutions. In this paper, we first highlight inherently built-in approximatio...

introduction: one of the major problems in the development of nuclear medicine images is the presence of noise. the noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a fourier transform environment. the main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Non-stationary signal processing applications use standard nonredundant DWT (Discrete Wavelet Transform) which is very powerful tool. But it suffers from shift sensitivity, absence of phase information, and poor directionality. To remove out these limitations, many researchers developed extensions to the standard DWT such as WP (Wavelet Packet Transform), and SWT (Stationary Wavelet Transform)....

Color image enhancement is a very important pre-processing stage in face detection and face recognition applications especially when the environment is very dark. In this paper, a color color image enhancement with the adaptive filter and discrete wavelet transform (DWT) is proposed. Discrete wavelet transform is used to improve image enhancement and stationary wavelet transform is used to redu...

This paper presents an adaptive harmonic current extraction scheme using notch filters combined with a modified discrete wavelet-packet transform (DWPT). The is applied to MMCC-STATCOM for mitigating harmonics distortion in power line. DWPT incorporates data expansion technique overcome the limitations of boundary effect. It identifies rms values dominant elements non-stationary real-time, thes...

Introduction: One of the major problems in the development of nuclear medicine images is the presence of noise. The noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a Fourier transform environment. The main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...