In this paper, a new algorithm for content− based image indexing and retrieval is presented. The proposed method is based on a combination of multiresolution analysis and color correlation histogram of the image. According to the new algorithm, wavelet coefficients of the image are computed first using Daubechies wavelets. A quantization step is then applied before computing horizontal and vert...

As shown by Dahmen, Harbrecht and Schneider [7, 23, 32], the fully discrete wavelet Galerkin scheme for boundary integral equations scales linearly with the number of unknowns without compromising the accuracy of the underlying Galerkin scheme. The supposition is a wavelet basis with a sufficiently large number of vanishing moments. In this paper we present several constructions of appropriate ...

A DSP engine for discrete wavelet transformation (DWT) is introduced in this paper. Serial processing DWT architecture provides a better speed and efficiency, makes DWT better choice for image processing than DCT. A dedicated hardware DWT architecture attached to a general purpose microprocessor provided the programmability of data access make possible for dynamic scheduling for various DSP app...

This paper presents a method of recognition of isolated offline handwritten Devanagari numerals using wavelets and neural network classifier. This method of optical character recognition takes the handwritten numeral image as input. After pre-processing, it is subjected to single level wavelet decomposition using Daubechies-4 wavelet filter. This wavelet decomposition allows viewing the input n...

The wavelet transform has been employed as an efficient method in image denoising via wavelet thresholding and shrinkage. The ridgelet transform was recently introduced as an alternative to the wavelet representation of two dimensional signals and image data. In this paper, a BayesShrink ridgelet denoising technique is proposed and its denoising performance is compared with a previous VisuShrin...

This paper describes an approach for texture characterization based on various wavelet decomposition transforms and its application for the discrimination of visually similar renal stone images. The proposed feature extraction algorithm applies Daubechies, Symlet, Coieflet, orthogonal and reverse biorthogonal wavelet transforms and uses approximation and detail coefficients to characterize rena...

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 ...

Orthogonal, semiorthogonal and biorthogonal wavelet bases are special cases of oblique multiwavelet bases. One of the advantage of oblique multiwavelets is the flexibility they provide for constructing bases with certain desired shapes and/or properties. The decomposition of a signal in terms of oblique wavelet bases is still a perfect reconstruction filter bank. In this paper, we present sever...

This paper describes WIPETM Wavelet Image Pornogra phy Elimination an algorithm capable of classifying an image as ob jectionable or benign The algorithm uses a combination of Daubechies wavelets normalized central moments and color histograms to provide semantically meaningful feature vector matching so that comparisons be tween the query image and images in a pre marked training set can be pe...

Wavelets have become a popular topic, especially in their use for image compression. Many papers have been written, but most are oriented toward mathematicians. This paper will present an application of the Daubechies wavelet for image compression with emphasis on the implementation and not on the mathematical analysis.