In this paper, high-efficient lifting-based architectures for the 5/3 forward and inverse discrete wavelet transform (DWT) are proposed. The proposed parallel and pipelined architecture consists of a horizontal filter (HF) and a vertical filter (VF). The system delays of the proposed architectures are reduced. Filter coefficients of the biorthogonal 5/3 wavelet low-pass filter are quantized bef...

Compressed sensing (CS) has been applied to accelerate magnetic resonance imaging (MRI) for many years. Due to the lack of translation invariance of the wavelet basis, undersampled MRI reconstruction based on discrete wavelet transform may result in serious artifacts. In this paper, we propose a CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet tra...

Image compression is a method through which we can reduce the storage space of images, videos which will helpful to increase storage and transmission process’s performance. In image compression, we do not only concentrate on reducing size but also concentrate on doing it without losing quality and information of image. In this paper, we present the comparison of the performance of Discrete cosi...

Denoising of real world images that are degraded by Gaussian noise is a long established problem in statistical signal processing. The existing models in time-frequency domain typically model the wavelet coefficients as either independent or jointly Gaussian. However, in the compression arena, techniques like denoising and detection, states the need for models to be nonGaussian in nature. Proba...

A novel vowel feature extraction method via hybrid wavelet and linear prediction coding (LPC) is presented here. The proposed Arabic vowels recognition system is composed of very promising techniques; wavelet transform (WT) with linear prediction coding (LPC) for feature extraction and feed forward backpropagation neural network (FFBPNN) for classification. Trying to enhance the recognition pro...

In this paper we consider the Easy Path Wavelet Transform (EPWT) on spherical triangulations. The EPWT has been introduced in [7] in order to obtain sparse image representations. It is a locally adaptive transform that works along pathways through the array of function values and exploits the local correlations of the data in a simple appropriate manner. In our approach the usual one-dimensiona...

Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...

The discrete wavelet transform (DWT) is incorporated into the JPEG baseline system for image coding. The discrete cosine transform (DCT) is replaced by an association of two-channel filter banks connected hierarchically. JPEG block-scanning and quantization schemes are adopted while we use JPEG’s entropy coder. The changes in scanning can be incorporated into the transform block in such a way t...

This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in...

Poor directional selectivity, a major disadvantage of the 2D separable discrete wavelet transform (DWT), has heretofore been circumvented either by using highly redundant, nonseparable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees. In this paper, we demonstrate that superior directional selectivity may be obtained with no redundancy in any separable wavele...