introduction:  breast  cancer  is  a  leading  cause  of  death  among  females  throughout  the  world.  currently,  radiologists are able to detect only 75% of breast cancer cases. making use of computer-aided design (cad)  can play an important role in helping radiologists perform more accurate diagnoses.   material and methods: using our hybrid method, the background and the pectoral muscle...

Denoising of images corrupted by Gaussian noise using wavelet transform is of great concern in the past two decades. In wavelet denoising method, detail wavelet coefficients of noisy image are thresholded using a specific thresholding function by comparing to a specific threshold value, and then applying inverse wavelet transform, results in denoised image. Recently, an effective image denoisin...

∗[email protected], Corresponding author 1 V er si on p re pr in t Comment citer ce document : Villa Vialaneix, N., Hernandez, N., Paris, A., Domange, C., Priymenko, N., Besse, P. (2016). On combining wavelets expansion and sparse linear models for regression on metabolomic data and biomarker selection. Communications in Statistics Simulation and Computation, 45 (1), 282-298. DOI : ...

Thresholding rules recently became of considerable interest when Donoho and John-stone applied them in the wavelet shrinkage context. Analytically simple, such rules are very eecient in data denoising and data compression problems. In this paper we nd hard thresholding decision rules that minimize Bayes risk for broad classes of underlying models. Standard Donoho-Johnstone test signals are used...

Results of lossy image compression using wavelet transforms and several thresholding techniques are presented here. The analyzed image was divided into little sub-images and each one was decomposed in a vector following a Hilbert fractal curve. The wavelet transform was applied to each vector and some of the high frequency components were suppressed based on some threshold criteria. Different l...

8 In this paper a method for detection of image forgery in lossy compressed digital images known as error level analysis (ELA) is presented and it’s noisy components are filtered with automatic wavelet soft-thresholding. With ELA, a lossy compressed image is recompressed at a known error rate and the absolute differences between these images, known as error levels, are computed. This method mig...

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. Noise severely limits the utility of the recorded ECG and thus need to be removed, for better clinical evaluation....

For signals belonging to balls in smoothness classes and noise with enough moments, the asymptotic behavior of the minimax quadratic risk among soft–threshold estimates is investigated. In turn, these results combined with a median filtering method lead to asymptotics for denoising heavy tails via wavelet thresholding. Some further comparisons of wavelet thresholding and of kernel estimators ar...