A new approach to pre-processing digital image for wavelet-based watermark

The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman–Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.     

Applying robust multibit watermarks to digital images

The current work is focusing on the implementation of a robust multibit watermarking algorithm for digital images, which is based on an innovative spread spectrum technique analysis. The paper presents the watermark embedding and detection algorithms, which use both wavelets and the Discrete Cosine Transform and analyzes the arising issues.     

3-D mesh sequence compression using wavelet-based multi-resolution analysis

In this paper, we present two compression methods for irregular three-dimensional (3-D) mesh sequences with constant connectivity. The proposed methods mainly use an exact integer spatial wavelet analysis (SWA) technique to efficiently decorrelate the spatial coherence of each mesh frame and also to adaptively transmit mesh frames with various spatial resolutions. To reduce the temporal redundancy, the first proposed method applies multi-order differential coding (MDC) to the temporal sequences obtained from SWA. MDC determines the optimal order of the differential coder by analyzing the variance of prediction errors. Comparing with the first order differential coding (FDC) scheme, the method can improve the compression performance. The second proposed method applies temporal wavelet analysis (TWA) to the temporal sequences. In particular, this method offers spatio-temporal multi-resolution coding. Through simulations, we prove that our methods enable efficient lossy-to-lossless compression for 3-D mesh sequences in a single frame work.     

Wavelet transforms and edge detectors on digital images

The paper investigates the problem of locating edges on digital images. The process is completed through various mathematical transforms. The edges are found by implementing mathematical algorithms for convolutions that are adapted to locate the edges and highlights the technique on using wavelet transforms. We are especially addressing the problem of edge detection, because it has far reaching applications to all fields and especially within medicine. A patient can be diagnosed as having an aneurysm by studying an angiogram. An angiogram is the visual view of the blood vessels whereby the edges are highlighted through the implementation of edge detectors. This process can be completed through wavelet transforms and other convolution techniques.     

An adaptive weighting parameter estimation between local and global intensity fitting energy for image segmentation

Local and global intensity fitting energy are widely used for image segmentation. In order to improve the segmentation quality in the presence of intensity inhomogeneity, in this paper, we propose a new adaptive rule for obtaining weighting parameter estimation between the local and global intensity fitting energy. Following the minimization of the energy functional, the value of the weighting parameter is dynamically updated with the contour evolution, which is effective and accurate for extracting the object.     

An exact construction of digital convex polygons with minimal diameter

Given a natural number n, an exact formula is derived for the minimal possible size MD(n) of a square grid, in which a digital convex n-gon can be inscribed. An exact construction of a digital convex n-gon which can be inscribed into a square grid of size MD(n) is also given.     

Convergence analysis of the Bregman method for the variational model of image denoising

The total variation model of Rudin, Osher, and Fatemi for image denoising is considered to be one of the best denoising models. Recently, by using the Bregman method, Goldstein and Osher obtained a very efficient algorithm for the solution of the ROF model. In this paper, we give a rigorous proof for the convergence of the Bregman method. We also indicate that a combination of the Bregman method with wavelet packet decomposition often enhances performance for certain texture rich images.     

Reconstruction of signals from multiscale edges

We present a method for signal reconstruction based upon the location of its singularities which are identified by a wavelet transform technique. The reconstructed signal is an infconvolution spline approximant. The data for the interpolation problem which we solve comes from a compact signal coding procedure. Error bounds and convergence results for the calculated signal are given.     

Partial differential equations and finite-difference methods in image processing,part 1: Image representation

Stochastic representation of discrete images by partial differential equation operators is considered. It is shown that these representations can fit random images, with nonseparable, isotropic covariance functions, better than other common covariance models. Application of these models in image restoration, data compression, edge detection, image synthesis, etc., is possible.Different representations based on classification of partial differential equations are considered. Examples on different images show the advantages of using these representations. The previously introduced notion of fast Karhunen-Loeve transform is extended to images with nonseparable or nearly isotropic covariance functions, or both.     

An integral transform associated to the Poisson integral and inversion of Flett potentials

We introduce a new weighted wavelet-like transform, generated by the Poisson integral and a “wavelet measure.” By making use of the relevant Calderón-type reproducing formula, we obtain an explicit inversion formula for the Flett potentials which are interpreted as negative fractional powers of the operator (E+Λ), where Λ=(−Δ)^1/2, Δ is the Laplacian and E is the identity operator.     

The expected profile of digital search trees

A digital search tree (DST) is a fundamental data structure on words that finds various applications from the popular Lempel-Ziv?78 data compression scheme to distributed hash tables. The profile of a DST measures the number of nodes at the same distance from the root; it depends on the number of stored strings and the distance from the root. Most parameters of DST (e.g., depth, height, fillup) can be expressed in terms of the profile. We study here asymptotics of the average profile in a DST built from sequences generated independently by a memoryless source. After representing the average profile by a recurrence, we solve it using a wide range of analytic tools. This analysis is surprisingly demanding but once it is carried out it reveals an unusually intriguing and interesting behavior. The average profile undergoes phase transitions when moving from the root to the longest path: at first it resembles a full tree until it abruptly starts growing polynomially and oscillating in this range. These results are derived by methods of analytic combinatorics such as generating functions, Mellin transform, poissonization and depoissonization, the saddle point method, singularity analysis and uniform asymptotic analysis.     

图像处理中全变差正则化数据拟合问题算法回顾

全变差正则化数据拟合问题产生于许多图像处理任务,如图像去噪、去模糊、图像修复、磁共振成像、压缩图像感知等.近年来,求解此类问题的快速高效算法发展很快.以最小二乘、最小一乘等为例简要回顾求解此类问题的主要算法,并讨论一个全变差正则化非凸数据拟合模型在脉冲噪声图像去模糊问题中的应用.     

Some remarks on “On the windowed Fourier transform and wavelet transform of almost periodic functions,” by J.R. Partington and B. Ünalmı

J.R. Partington and B. Ünalmı consider in their 2001 paper [J.R. Partington, B. Ünalmı , Appl. Comput. Harmon. Anal. 10 (1) (2001) 45–60] the windowed Fourier transform and wavelet transform as tools for analyzing almost periodic signals. They establish Parseval-type identities and consider discretized versions of these transforms in order to construct generalized frame decompositions. We have found a gap in the construction of generalized frames in the windowed Fourier transform case; we comment on this gap and give an alternative proof. As for the wavelet transform case, in [J.R. Partington, B. Ünalmı , Appl. Comput. Harmon. Anal. 10 (1) (2001) 45–60] the generalized frame decomposition is done only for the simplest wavelet, the Haar wavelet; we show how to construct generalized frame decompositions for a wide family of wavelets.     

An inequality for sums of binary digits, with application to Takagi functions

Let ?(x)=2inf{|x−n|:n∈Z}, and define for α>0 the function

     

The Laplace transform of the digamma function: An integral due to Glasser, Manna and Oloa

The definite integral

is related to the Laplace transform of the digamma function

by when . Certain analytic expressions for in the complementary range, , are also provided.

     

An adaptive,multilevel scheme for the implicit solution of three‐dimensional phase‐field equations

Phase‐field models, consisting of a set of highly nonlinear coupled parabolic partial differential equations, are widely used for the simulation of a range of solidification phenomena. This article focuses on the numerical solution of one such model, representing anisotropic solidification in three space dimensions. The main contribution of the work is to propose a solution strategy that combines hierarchical mesh adaptivity with implicit time integration and the use of a nonlinear multigrid solver at each step. This strategy is implemented in a general software framework that permits parallel computation in a natural manner. Results are presented that provide both qualitative and quantitative justifications for these choices.© 2010 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2010     

AN ASYMPTOTIC ORDER OFFOURIER TRANSFORM ON SL（2,R）

In this paper, a better asymptotic order of Fourier transform on SL(2,R) is obtained by using classical analysis and Lie analysis comparing with that of [5]、[6], and the Plancherel theorem on Cc^2(SL(2,R) ) is also obtained as an application.