The denoising of video data should take into account both temporal and spatial dimensions, however, true 3D transforms are rarely used for video denoising. Separable 3-D transforms have artifacts that degrade their performance in applications. This paper describes the design and application of the non-separable oriented 3-D dual-tree wavelet transform for video denoising. This transform gives a...

This paper presents a new signal denoising method based on the classical three step procedure analysis-thresholdsynthesis and the Spectral Intrinsic Decomposition (SID). This method consists of an iterative thresholding of the SID components. If the wavelets denoising approach depends on the choice of the wavelet form, the SID-denoising proposed in this paper is self adaptive. The SID-based rem...

Estimating the images using decimated wavelet transform is very popular technique in different applications. In this paper a new thresholding function with combination of Smoothly Clipped Absolute Deviation (SCAD), Hard thresholding and soft thresholding functions are introduced for wavelet based denoising of images. The proposed technique is applied for denoising of noisy images contaminated w...

An electrocardiogram (ECG) is a recording of the electrical activity of the heart in dependence on time. The mechanical activity of the heart is linked with its electrical activity. Therefore ECG is an important diagnostic tool for assessing heart function. It becomes necessary to make ECG signals free from noise for proper analysis and detection of the diseases. Various noise removal technique...

This thesis focuses on denoising of positron emission tomography (PET) data. Cardiac PET scans generated using a rubidium-82 radiotracer are a convenient, non– invasive method of diagnosing heart disease, but suffer from a high degree of noise. Denoising methods based on the wavelet transform are capable of outperforming existing clinical methods due to their ability to better preserve detail w...

Empirical mode decomposition (EMD) is one of the most efficient methods used for nonparametric signal denoising. In this study wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. The principles of hard and soft wavelet thresholding including translation invariant denoising were appropriately modified to develop denoising methods suited for ...

With the widespread use of videos in many fields of our lives, it becomes very important to develop new techniques for video denoising. Spatial video denoising using wavelet transform has been the focus of the current research, as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered ...

In this paper, we propose a new wavelet denoising method with edge preservation for digital images. Traditionally, most denoising methods assume additive Gaussian white noise or statistical models; however, we do not make such an assumption here. Briefly, the proposed method consists of a combination of dyadic lifting schemes and edge-preserving wavelet thresholding. The dyadic lifting schemes ...

In this paper, we study denoising of multicomponent images. The presented procedures are spatial wavelet-based denoising techniques, based on Bayesian leastsquares optimization procedures, using prior models for the wavelet coefficients that account for the correlations between the spectral bands. We analyze three mixture priors: Gaussian scale mixture models, Bernoulli-Gaussian mixture models ...

This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard dev...