Data compression of power quality events using the slantlet transform

Power Quality Disturbance Data Compression Using Wavelets Transform

Abstract---In this paper we present a wavelet compression technique for power quality disturbance data. Power quality transient data are compressed and stored for analysis and classification purposes. Original data can be reconstructed and then analyzed using wavelet transform. Different power quality disturbances including voltage sag, swell, sag with harmonic and swell with harmonics are used...

Analysis of Power System Disturbance Signals using Slantlet Transform for Compression and Denoising

An orthogonal discrete wavelet transform (DWT) is a slantlet transform (SLT) with two zero moments and having improved time localization. SLT retains usual characteristics of filter bank implementation with a scale dilation factor of two. The basis is based on filter bank which uses different filters for different scales, is piecewise linear unlike iterated filter bank in DWT. This paper discus...

The slantlet transform

The discrete wavelet transform (DWT) is usually carried out by filterbank iteration; however, for a fixed number of zero moments, this does not yield a discrete-time basis that is optimal with respect to time localization. This paper discusses the implementation and properties of an orthogonal DWT, with two zero moments and with improved time localization. The basis is not based on filterbank i...

Power Quality Data Compression

Slantlet Transform and Phase Congruency based Image Compression

Image compression is an active area of research with a wide range of applications. Being able to represent an image with lesser number of coefficients, without affecting the image quality has been the prime aim of image compression. In this research, a new image compression technique has been proposed, based on Slantlet Transform and the principle of Phase Congruency. The compressed image quali...