In this paper, a new method for blind watermarking is used to achieve robustness against SPIHT compression methods as well as some other well known attacks such as Histogram Equalization, Gamma Correction, median noise, salt and pepper noise. The watermark is encoded via singular value decomposition and later embedded. Then we apply discrete wavelet transform (Haar) at one level and the waterma...

In order to get an efficient image representation we introduce a new adaptive Haar wavelet transform, calledTetrolet Transform. Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. The corresponding filter bank algorithm is simple but enormously effective. Numerical results show the strong efficiency of the tetrolet transf...

The wavelet transform has become a useful computational tool for a variety of signal and image processing applications. For example, the wavelet transform is useful for the compression of digital image files; smaller files are important for storing images using less memory and for transmitting images faster and more reliably. The FBI uses wavelet transforms for compressing digitally scanned fin...

A Haar wavelet based numerical method for solving singularly perturbed linear time invariant system is presented in this paper. The reduced pure slow and pure fast subsystems are obtained by decoupling the singularly perturbed system and differential matrix equations are converted into algebraic Sylvester matrix equations via Haar wavelet technique. The operational matrix of integration and its...

Classification of iris templates based on their texture patterns is one of the most effective methods in iris recognition systems. This paper proposes a novel algorithm for automatic iris classification based on fractal dimensions of Haar wavelet transforms is presented. Fractal dimensions obtained from multiple scale features are used to characterize the textures completely. Haar wavelet is ap...

In this paper we focus on image segmentation by proposing a new algorithm based on Haar wavelet decomposition and Kmeans algorithm. When Haar wavelet decomposition is applied to an image it gives an idea about high frequency components. If higher levels of decomposition are performed, different texture region information can be captured. The paper deals with the texture segmentation of an image...

We use Cramér-Chernoff type estimates in order to study the Calderón-Zygmund structure of kernels ? I ? D a ( ? ) ? x y , and their concentration about mean, where are subgaussian independent random variables { : } is wavelet basis dyadic intervals R . consider both, cases standard smooth wavelets case Haar wavelet.

This paper deals with Szegö type limits for multiplication operators on L(R) with respect to Haar orthonormal basis. Similar studies have been carried out by Morrison for multiplication operators Tf using Walsh System and Legendre polynomials [14]. Unlike the Walsh and Fourier basis functions, the Haar basis functions are local in nature. It is observed that Szegö type limit exist for a class o...