The scheme proposed in this paper combines independent components analysis (ICA) with discrete wavelet transform (DWT) and discrete cosine transform (DCT). Firstly, the original image is decomposed by 2-D DWT and the detail sub-bands are reserved. Then, the approximate image is transformed by DCT and embedded with watermark. The watermark is detected through ICA. The simulation results demonstr...

Images can be compressed in multiple ways. The new JPEG2000 standard uses an algorithm called EBCOT and the Discrete Wavelet Transform, while the ordinary JPEG standard uses the Discrete Cosine Transform (DCT). Other compression methods use frequency-domain analysis with Gabon Filters, Radon Filters and other Wavelet Filters. Sim et al.[2] present an algorithm for obtaining texture descriptors ...

there are a variety of electrocardiogram (ecg) based methods to detect myocardial infarction (mi) patients. this study used the signal averaged electrocardiogram (saecg) and its wavelet coefficient as an index to detect mi. orthogonal leads signals from 50 acute myocardial infarction (ami) and 50 healthy subjects were selected from the national metrology institute of germany (ptb diagnostic dat...

Abstract It is shown how a modern extension of Fourier analysis known as wavelet analysis is applied to signals containing multiscale information. First, a continuous wavelet transform is used to analyse the spectrum of a nonstationary signal (one whose form changes in time). The spectral analysis of such a signal gives the strength of the signal in each frequency as a function of time. Next, t...

We study the scaling behavior of the fluctuations, as extracted through wavelet coefficients based on discrete wavelets. The analysis is carried out on a variety of physical data sets, as well as Gaussian white noise and binomial multi-fractal model time series and the results are compared with continuous wavelet based average wavelet coefficient method. It is found that high-pass coefficients ...

This paper presents a comparative study of different wavelet denoising techniques and the results obtained were examined. The denoising process rejects noise by thresholding in the wavelet domain. It is observed that „rigrsure„ method gives optimum performance. Discrete wavelet transform has the benefit of giving a joint timefrequency representation of the signal. Also it is suitable for both s...

Abstract—A new interpretation for the wavelet analysis is reported, which can is viewed as an information processing technique. It was recently proposed that every basic wavelet could be associated with a proper probability density, allowing defining the entropy of a wavelet. Introducing now the concept of wavelet mutual information between a signal and an analysing wavelet fulfils the foundati...

In this paper, the influence of four key issues on wavelet-based analysis of hydrologic series’ complexity under multi-temporal scales, including the choice of mother wavelet, noise, estimation of probability density function and trend of series data, was first studied. Then, the complexities of several representative hydrologic series data were quantified and described, based on which the perf...

Though frequently and commonly applied to discrete-time processes, the discrete wavelet transform is de"ned only for, and should therefore strictly speaking be applied only to, continuous-time processes. We provide a method for applying it to intrinsically discrete data, in such a way that the spectrum of discrete second-order processes can be meaningfully studied. The practical step required i...

In this paper, a new approach (scheme) to the analysis of quad-trees in the discrete wavelet spectrum of a digital image is proposed. During the pre-scanning phase, the proposed scheme generates problem-oriented binary codes for the whole set of quad-tree roots (wavelet coefficients) and thereby accumulates information on the significance of respective descendants (wavelet coefficients comprisi...