In this paper a watermarking method based on the Haar wavelet transform is proposed. The hiding procedure is performed in the LL subband of the first level of Haar decomposition of the image. The coefficients resilient to specific attacks are modified in order to obtain a robust embedding scheme. The proposed method is used to define a mask to perform the embedding in the wavelet transform doma...

Many global illumination algorithms generate directionally-and positionally-varying radiance data that then need to be somehow re-sampled and used for nal shading. This operation should lter all light over the incident hemisphere through the BRDF to generate an accurate image. This can be done analytically for simple BRDFs, such as Lambertian or Phong-like BRDFs, but becomes more diicult in the...

The multiresolution time-domain (MRTD) algorithm is applied to the problem of general two-dimensional electromagnetic scattering. A Haar wavelet expansion is utilized. A parallel between Haar MRTD and the classic Yee finite difference time-domain (FDTD) algorithm is discussed, and results of simulations on canonical targets are shown for comparison. We focus on the incident-field implementation...

In this paper, we proposed a new method to develop secure image-encryption techniques using a logistics -based encryption algorithm. In this technique, a Haar wavelet transform was used to decompose the image and decorrelate its pixels into averaging and differencing components. The logistic based encryption algorithm produces a cipher of the test image that has good diffusion and confusion pro...

We propose a new “Haar-Fisz” technique for estimating the time-varying, piecewise constant local variance of a locally stationary Gaussian time series. We apply our technique to the estimation of the spectral structure in the Locally Stationary Wavelet model. Our method combines Haar wavelets and the variance stabilizing Fisz transform. The resulting estimator is mean-square consistent, rapidly...

In our previous work, we showed empirically that independent (Haar) wavelet models were parsimonious, computationally efficient and accurate in modeling heterogeneous network traffic measured by both auto-covariance functions and buffer loss rate. We also proved analytically that such models were capable of capturing any decay rate of auto-covariance functions at large lags. But the simplicity ...

The purpose is to study qualitative and quantitative rates of image compression by using different Haar wavelet banks. The experimental results of adaptive compression are provided. The paper deals with specific examples of orthogonal Haar bases generated by multiresolution analysis. Bases consist of three piecewise constant wavelet functions with a support $[0,1] \times [0,1] $.

With the development of steganalysis, the security of steganography is faced with tremendous challenge. High order statistical analysis is an effective and common detecting method that can defeat many hiding scheme. This paper proposes a secure steganography that can effectively resist image steganalysis based on high order statistical analysis. We have analyzed Haar wavelet decomposition chara...

Metode Wavelet merupakan salah satu metode yang unggul untuk menganalisis serta mengekstraksi ciri isyarat suara tutur. Dalam proses ekstraksi menggunakan Wavelet, terdapat beberapa faktor dapat berpengaruh dalam mendapatkan bersifat diskriminan, diantaranya: pemilihan mother wavelet, sub-band, dan level dekomposisi. Beberapa contoh sering digunakan Daubechies, Coiflet, Meyer, Haar, Symlet, Bio...

An orthogonal Haar scattering transform is a deep network computed with a hierarchy of additions, subtractions and absolute values over pairs of coefficients. Unsupervised learning optimizes Haar pairs to obtain sparse representations of training data with an algorithm of polynomial complexity. For signals defined on a graph, a Haar scattering is computed by cascading orthogonal Haar wavelet tr...