We propose a block-based wavelet codec in which motion vector estimation and motion residual encoding are performed within a wavelet domain. By interpolation on dyadic wavelet transform, we show that motion vector estimation in the wavelet domain can achieve sub-pixel precision. To improve PSNR performance at low bit rates, we propose a bit-plane-based rate-distortion (R-D) optimization algorit...

This paper studies 2D and 3D wavelet domain medical image resolution enhancement method. The proposed approach is based on the interpolation of the low resolution input image and the derived high frequency sub-band images obtained using Discrete Wavelet Transform (DWT). Experimental results on both 2D and 3D images show how our method enhances the image’s details and preserves edges.

In video surveillance, identification is a very significant element for target tracking, activity recognition, traffic monitoring, military etc. The identification process classifies the pixels into either foreground or background and a common approach used to achieve such a classification is background removal. A Novel method is proposed for the moving object detection based on Modular Wavelet...

This paper extends the technique used for Document Text Extraction from Images using 2-D Haar Wavelet. The discrete wavelet transform is a very useful tool for signal analysis and image processing, especially in multi-resolution representation. It can decompose signal into different components in the frequency domain. Two-dimensional discrete wavelet transform (2-D DWT) decomposes an input imag...

In this article, we introduce the concept of fractional wavelet transform. Using a two-channel unbalanced lifting structure it is possible to decompose a given discrete-time signal x[n] sampled with period T into two sub-signals x1[n] and x2[n] whose average sampling periods are pT and qT , respectively. Fractions p and q are rational numbers satisfying the condition: 1/p+ 1/q = 1. The low-band...

The paper presents a new digital image hiding algorithm based on wavelet packets transform and singular value decomposition. The low-frequency sub-band of wavelet packets transform has strong antijamming capacity and the singular value has very strong stability. The presented algorithm implements bit plane decomposition on the secret image and wavelet packet decomposition on the carrier image. ...

The features of dynamic, noise and instability, make the network traffic eruptive and unstable, and this obstructs the network traffic prediction. In order to figure out its characteristics and developing tendency accurately, the paper proposes a wavelet-transform-based prediction algorithm: Firstly, with the multi-resolution analysis of wavelet transform, the network traffic, which is difficul...

Nowadays Epileptic disorder is a most challenge aspects in brain activation. Electroencephalograph (EEG) is one of the popular procedures to understand the human brain condition. The activation of brain will be changed due to the symptoms of neurological disorder. We have been proposed a procedure to find epilepsy disorder, using discrete wavelet transform and neural network classifier. The EEG...

Compressive Sensing(CS) theory can reconstruct the original images from the less measurements with using the priors of the image sparse representation. The CS theory is applied into the video super-resolution(SR) reconstruction, and a new algorithm based on wavelet transform is proposed in this paper. Firstly, wavelet transform is used to decompose the low resolution image so as to get the low ...

In this paper, we present nonlinear interpolation schemes for image resolution enhancement. The Multilayer perceptron (MLP) interpolation schemes based on the wavelet transform and subband filtering are proposed. Because estimating each sub-image signal is more effective than estimating the whole image signal, pixels in the low-resolution image are used as input signal of the MLP to estimate al...