While there is a very long tradition of approximating a data array by projecting row or column vectors into a lower dimensional subspace the direct approximation of a data matrix through smoothing is less common. Applications of data array smoothing include visualization; filtering of less relevant, and thus harder to interpret, values; and as a means towards compression. Wavelet smoothing or r...

It is well known that the commonly used separable extensions of one-dimensional transforms, such as the wavelet transform, have limitations in capturing the geometry of image edges. But natural scene images always have geographic lines, such as textures, edges which can not be well reconstructed when compressed by using one-dimensional transform. So in lossy compression of images, it is importa...

This paper presents parallel algorithms for computing multi-dimensional wavelet transforms on both shared memory and distributed memory machines. Traditional data partitioning methods for n-dimensional Discrete Wavelet Transforms (DWTs) call for data redistribution once a one dimensional wavelet transform is computed along each dimension. To avoid the data communication inherent in this redistr...

We discuss the shift invariant properties of a new implementation of the Discrete Wavelet Transform, which employs a dual tree of wavelet lters to obtain the real and imaginary parts of complex wavelet co-eecients. This introduces limited redundancy (2 m :1 for m-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective lters (properties l...

The wavelet transform has emerged as a cutting edge technology, in the field of image compression. Wavelet-based coding provides substantial improvements in picture quality at higher compression ratios. In this paper an approach is proposed for the compression of an image using 5/3(lossless) Integer discrete wavelet transform (DWT) for Image Compression. The proposed architecture, based on new ...

Multi-resolution analysis of digital image has attracted numerous studies since dyadic wavelet transform was introduced to this field. Aiming at achieving accurate and stationary edge detection, an improved Mallat wavelet decomposition algorithm was employed. This algorithm was defined by a low frequency component and three high frequency components. Two-dimensional signal can be reconstructed ...

We introduce a new locally adaptive wavelet transform, called Easy Path Wavelet Transform (EPWT), that works along pathways through the array of function values and exploits the local correlations of the data in a simple appropriate manner. The usual discrete orthogonal and biorthogonal wavelet transform can be formulated in this approach. The EPWT can be incorporated into a multiresolution ana...

In this paper, we develop the theory of the wavelet transform over Galois elds. To avoid the limitations inherent in the number theoretic Fourier transform over nite elds, our wavelet transform relies on a basis decomposition in the time domain rather than in the frequency domain. First, we characterize the in nite dimensional vector spaces for which an orthonormal basis expansion of any sequen...

Compression technique is significant in day to day scenario for smooth transmission of data. By utilizing this technique the bandwidth utilization is reduced. Even compression techniques help us for efficient memory utilization to make overall data transmission better. Data size in different cases is quite huge and difficult to send without compressing it. In the biomedical arena, it is applica...