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...

The shift-variant property of the discrete wavelet transform (DWT) makes the motion estimation and compensation ine$cient in the wavelet domain. In order to overcome the shift-variant property of the DWT, a low-band-shift (LBS) method has been developed. Using the LBS method in the wavelet domain, two motion estimation and compensation schemes are developed and evaluated. One scheme is the moti...

Wavelet-based image denoising algorithm depends upon the energy compaction property of wavelet transforms. However, for many real-world images, we cannot expect good energy compaction in a single wavelet domain, because most real-world images consist of components of a variety of smoothness. We can relieve this problem by using multiple wavelet bases to match different characteristics of images...

An efficient numerical quadrature for the calculation of the potential energy of wavefunctions expressed in the Daubechies wavelet basis. Abstract. An efficient numerical quadrature is proposed for the approximate calculation of the potential energy in the context of pseudo potential electronic structure calculations with Daubechies wavelet and scaling function basis sets. Our quadrature is als...

In this work. we present a novel method of object recognition and feature generation based on multiscale object descriptions obtained using wavelet networks in combination with morphological filtering. First, morphological filtering techniques are used to obtain structural information about the object. Then, wavelet networks are used to extract or capture geometric information about an object a...

Orthogonal and Symmetric Haar Wavelets on the Sphere Christian Lessig Master of Science Graduate Department of Computer Science University of Toronto 2007 The efficient representation of signals defined over spherical domains has many applications. We derive a new spherical Haar wavelet basis (SOHO) that is both orthogonal and symmetric, rebutting previous work that presumed the nonexistence of...

The main task in wavelet analysis (decomposition and reconstruction) is to find a good wavelet function (mother wavelet) to perform an optimal decomposition. The goal of most wavelet researches is to create a set of basis functions and transforms that will give an informative, efficient and useful description of a signal. It is better if the wavelet function is adapted to the signal, because th...

It is commonly known that wavelet expansions are very sensitive to translation of an input signal due to their dyadic structure. Without proper time alignment of the signal to the decomposition basis vectors, a compact expansion may be unattainable. Recently, work has been done to combat translation sensitivity by determining the best translation-invariant expansion of a signal with respect to ...

This paper describes a novel method of character recognition targeted for extracting complex annotations found in engineering documents. The results of this work will make it possible to capture the information contained in documents used to support facilities management and manufacturing. The recognition problem is made difficult in part because characters and text may be expressed in arbitrar...