Search results for "Wavelet transform"
showing 10 items of 146 documents
Efficient image compression using directionlets
2007
Directionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments imposed along different directions. We combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional wavelet transform. We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the sta…
Hilbert-Huang versus morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm
2009
Background. Compared to the waveform or spectrum analysis of event-related potentials (ERPs), time-frequency representation (TFR) has the advantage of revealing the ERPs time and frequency domain information simultaneously. As the human brain could be modeled as a complicated nonlinear system, it is interesting from the view of psychological knowledge to study the performance of the nonlinear and linear time-frequency representation methods for ERP research. In this study Hilbert-Huang transformation (HHT) and Morlet wavelet transformation (MWT) were performed on mismatch negativity (MMN) of children. Participants were 102 children aged 8–16 years. MMN was elicited in a passive oddbal…
Wavelet and fractal approach to surface roughness characterization after finish turning of different workpiece materials
2009
In this paper, the surface profiles generated in longitudinal turning operations were characterized using continuous wavelet transform (CWT) and normalized fractal dimension Dn. In the comparative analysis, some characteristic roughness profiles after the turning of different workpiece materials, such as C45 medium carbon steel, nodular cast iron and hardened (55 HRC) high-strength alloy steel were selected. For wavelet characterization, both Morlet and ‘Mexican hat’ analyzing wavelets, which allow the assessment of extrema and frequency distribution, were utilized. The results of the CWT as a function of profile and momentary wavelet length are presented. It is concluded that CWT can be us…
Local Structure of Multiferroic MnWO4 and Mn0.7Co0.3WO4 Revealed by the Evolutionary Algorithm
2015
A novel reverse Monte Carlo/evolutionary algorithm scheme was applied to the analysis of the W L3-edge and Mn(Co) K-edges EXAFS spectra from multiferroic MnWO4 and Mn0.7Co0.3WO4. A 3D structural model, consistent with the experimental data, was obtained, and the influence of composition and temperature on the local structure of tungstates is discussed.
Reverse Monte Carlo modeling of thermal disorder in crystalline materials from EXAFS spectra
2012
Abstract In this work we present the Reverse Monte Carlo (RMC) modeling scheme, designed to probe the local structural and thermal disorder in crystalline materials by fitting the wavelet transform (WT) of the EXAFS signal. Application of the method to the analysis of the Ge K-edge and Re L3-edge EXAFS signals in crystalline germanium and rhenium trioxide, respectively, is presented with special attention to the problem of thermal disorder and related phenomena.
Subsignal-based denoising from piecewise linear or constant signal
2011
15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…
Signal Restoration via a Splitting Approach
2012
International audience; In the present study, a novel signal restoration method from noisy data samples is presented and is termed as "signal split (SSplit)" approach. The new method utilizes Stein unbiased risk estimate estimator to split the signal, the Lipschitz exponents to identify noise elements and a heuristic approach for the signal reconstruction. However, unlike many noise removal techniques, the present method works only in the non-orthogonal domain. Signal restoration was performed on each individual part by finding the best compromise between the data samples and the smoothing criteria. Statistical results are quite promising and suggest better performance than the conventional…
A Watermarking of Medical Image : New Approach Based On "Multi-Layer" Method
2011
In order to contribute to security sharing and transmission of medical images, this paper propose a new approach for Watermarking image based on the techniques of Code Division Multiple Access (CDMA), Discrete Wavelet transform (DWT) and Error Correcting Code (ECC). The motivation of this approach is to improve the quantity of data integration with the conservation of the image visual quality. Therefore, this work permits to the user the capacity to correct the possible alterations if it exists. IRM and Echographic medical image are used to experiment this approach.
Multi-focus image fusion using local variability
2018
In this thesis, we are interested in the multi-focus image fusion method. This technique consists of fusing several captured images with different focal lengths of the same scene to obtain an image with better quality than the two source images. We propose an image fusion method based on Laplacian pyramid technique using Discrete Wavelet Transform (DWT) as a selection rule. We then develop two multi-focus image fusion methods based on the local variability of each pixel. It takes into account the information in the surrounding pixel area. The first method is to use local variability as an information in the Dempster-Shafer theory. The second method uses a metric based on local variability. …
Discrete wavelet transform implementation in Fourier domain for multidimensional signal
2002
Wavelet transforms are often calculated by using the Mallat algorithm. In this algorithm, a signal is decomposed by a cascade of filtering and downsampling operations. Computing time can be important but the filtering operations can be speeded up by using fast Fourier transform (FFT)-based convolutions. Since it is necessary to work in the Fourier domain when large filters are used, we present some results of Fourier-based optimization of the sampling operations. Acceleration can be obtained by expressing the samplings in the Fourier domain. The general equations of the down- and upsampling of digital multidimensional signals are given. It is shown that for special cases such as the separab…