In our contribution, we compute new edge wavelet filters for image compression and we compare errors for several image compression techniques. Our numerical experiments confirm the theoretical assumption that the error of the compression is smaller for the discrete wavelet transform with derived edge filters than for other methods using an extension of an image.

Ocean remotely sensed image analysis using two-dimensional continuous wavelet transforms Li-Chung Wu a , Laurence Zsu-Hsin Chuang b , Dong-Jiing Doong c & Chia Chuen Kao a a Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan, Taiwan b Institute of Ocean Technology and Marine Affairs, National Cheng Kung University, Tainan, Taiwan c Department of Marine Environ...

Discrete-time wavelet transform (DWT) is found to be better than other transforms in the time-varying system analysis, e.g. for time-varying parametric modelling [16], time-varying systems identification [17], time-varying parameter estimation [18] and time domain signal analysis [19]. In the literature the common method to analyze the time-varying system using discrete-time wavelet transform i...

introduction: one of the major problems in the development of nuclear medicine images is the presence of noise. the noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a fourier transform environment. the main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Entropy as a measure of uncertainty was used to represent the results of the wavelet technique in electrochemical noise analysis. The experimental signals were obtained by recording the electrochemical potential and current noise of 7075 aluminum alloy in 3.5% NaCl solution. The electrochemical potential and current noise were decomposed into 16 levels using Daubechies wavelets. Wavelet output ...

This term project report introduces the well-know Gabor wavelet transform and its applications. Wavelet transform could extract both the time (spatial) and frequency information from a given signal, and the tunable kernel size allows it to perform multi-resolution analysis. Among kinds of wavelet transforms, the Gabor wavelet transform has some impressive mathematical and biological properties ...

Power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed for detecting types of transmission line faults. In this paper, a comparative study of wavelet based de-noising signal based on wavelet thresholding is proposed. Discrete Wavelet Transform (DWT) analysis of the transient disturbance caused as a result of occurrence some of...

abstract most structural failures are because of break in consisting materials. these breaks are initiated with crack extension, which is a serious threat to the behavior of structure, so different methods have been developed for distinguishing and showing such cracks. meanwhile, the new methods based on original wavelet transform are efficient and very important in the subject of signals. the ...

entropy as a measure of uncertainty was used to represent the results of the wavelet technique in electrochemical noise analysis. the experimental signals were obtained by recording the electrochemical potential and current noise of 7075 aluminum alloy in 3.5% nacl solution. the electrochemical potential and current noise were decomposed into 16 levels using daubechies wavelets. wavelet output ...

In this paper, we proposed a new artifact level estimation algorithm. The noise model is firstly proposed and 2D discrete wavelet transform is explained. The proposed method is based on Donoho’s approach. From the result section, it is obvious that the proposed method gives favorable results.