Polarization Analysis in the Discrete Wavelet Domain: An Application to Volcano Seismology

2010 ◽  
Vol 100 (2) ◽  
pp. 670-683 ◽  
Author(s):  
L. D'Auria ◽  
F. Giudicepietro ◽  
M. Martini ◽  
M. Orazi ◽  
R. Peluso ◽  
...  
Keyword(s):  
Discrete Wavelet ◽  
Volcano Seismology ◽  
Wavelet Domain ◽  
Polarization Analysis

Denoising of magnetotelluric signals by polarization analysis in the discrete wavelet domain

2017 ◽  
Vol 100 ◽  
pp. 135-141 ◽  
Author(s):  
R. Carbonari ◽  
L. D'Auria ◽  
R. Di Maio ◽  
Z. Petrillo
Keyword(s):  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Polarization Analysis

Multifocus image fusion based on coefficient significance of redundant discrete wavelet transform

2019 ◽  
Vol 46 (3) ◽  
pp. 377-383
Author(s):  
Jianhua Liu ◽  
Peng Geng ◽  
Hongtao Ma
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Fusion Rule ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Content Type ◽  
Ripplet Transform ◽  
Detail Coefficient ◽  
Redundant Discrete Wavelet Transform

Purpose This study aims to obtain the more precise decision map to fuse the source images by Coefficient significance method. In the area of multifocus image fusion, the better decision map is very important the fusion results. In the processing of distinguishing the well-focus part with blur part in an image, the edge between the parts is more difficult to be processed. Coefficient significance is very effective in generating the better decision map to fuse the multifocus images. Design/methodology/approach The energy of Laplacian is used in the approximation coefficients of redundant discrete wavelet transform. On the other side, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient. Findings Due to the shift-variance of the redundant discrete wavelet and the effectiveness of fusion rule, the presented fusion method is superior to the region energy in harmonic cosine wavelet domain, pixel significance with the cross bilateral filter and multiscale geometry analysis method of Ripplet transform. Originality/value In redundant discrete wavelet domain, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient of source images.

Self-Embedding Watermarking Scheme based on Discrete Wavelet Domain

2018 ◽  
Author(s):  
Hanen Rhayma ◽  
Achraf Makhloufi ◽  
Habib Hamam ◽  
Ahmed Ben Hamida
Keyword(s):  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Watermarking Scheme

scholarly journals Image enhancement in wavelet domain based on histogram equalization and median filter

2021 ◽  
Author(s):  
Haval Sulaiman Abdullah ◽  
◽  
Firas Mahmood Mustafa ◽  
Atilla Elci ◽  
◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Noise Reduction ◽  
Discrete Wavelet Transform ◽  
Image Enhancement ◽  
Median Filter ◽  
Histogram Equalization ◽  
Image Noise ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Image Noise Reduction

During the acquisition of a new digital image, noise may be introduced as a result of the production process. Image enhancement is used to alleviate problems caused by noise. In this work, the purpose is to propose, apply, and evaluate enhancement approaches to images by selecting suitable filters to produce improved quality and performance results. The new method proposed for image noise reduction as an enhancement process employs threshold and histogram equalization implemented in the wavelet domain. Different types of wavelet filters were tested to obtain the best results for the image noise reduction process. Also, the effect of canceling one or more of the high-frequency bands in the wavelet domain was tested. The mean square error and peak signal to noise ratio are used for measuring the improvement in image noise reduction. A comparison made with two related works shows the superiority of the methods proposed and implemented in this research. The proposed methods of applying the median filter before and after the histogram equalization methods produce improvement in performance and efficiency compared to the case of using discrete wavelet transform only, even with the cases of multiresolution discrete wavelet transform and the cancellation step.

scholarly journals Spatial downscaling of radar-derived rainfall field by two-dimensional wavelet transform

2020 ◽  
Vol 51 (3) ◽  
pp. 456-469
Author(s):  
Vahid Nourani ◽  
Armin Farshbaf ◽  
S. Adarsh
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet ◽  
Main Concern ◽  
Two Dimensional ◽  
Wavelet Domain ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Pattern Display ◽  
Actual Size ◽  
Good Agreement

Abstract Downscaling of rainfall fields, either as images or products of global circulation models, have been the motive of many hydrologists and hydro-meteorologists. The main concern in downscaling is to transform high-resolution properties of the rainfall field to lower resolution without introducing erroneous information. In this paper, rainfall fields obtained from Next Generation Weather Surveillance Radar (NEXRAD) Level III were examined in the wavelet domain which revealed sparsity for wavelet coefficients. The proposed methodology in this work employs a concept named Standardized Rainfall Fluctuation (SRF) to overcome the sparsity of rainfall fields in wavelet domain which also exhibited scaling behaviors in a range of scales. SRFs utilizes such scaling behaviors where upscaled versions of the rainfall fields are downscaled to their actual size, using a two-dimensional discrete wavelet transform, to examine the reproduction of the rainfall fields. Furthermore, model modifications were employed to enhance the accuracy. These modifications include removing the negative values while conserving the mean and applying a non-overlapping kernel to restore high-gradient clusters of rainfall fields. The calculated correlation coefficient, statistical moments, determination coefficient and spatial pattern display a good agreement between the outputs of the downscaling method and the observed rainfall fields.

scholarly journals Two-Layer Fragile Watermarking Method Secured with Chaotic Map for Authentication of Digital Holy Quran

2014 ◽  
Vol 2014 ◽  
pp. 1-29 ◽  
Author(s):  
Mohammed S. Khalil ◽  
Fajri Kurniawan ◽  
Muhammad Khurram Khan ◽  
Yasser M. Alginahi
Keyword(s):  
Wavelet Transforms ◽  
Wavelet Coefficient ◽  
Chaotic Map ◽  
Spatial Domain ◽  
Fragile Watermarking ◽  
Discrete Wavelet ◽  
Discrete Wavelet Transforms ◽  
Wavelet Domain ◽  
Good Image Quality ◽  
Holy Quran

This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small.

scholarly journals A New Approach to Nonsinusoidal Steady-State Power System Analysis

2009 ◽  
Vol 2009 ◽  
pp. 1-18
Author(s):  
A. Ketabi ◽  
M. Khoshkholgh ◽  
R. Feuillet
Keyword(s):  
Steady State ◽  
Power System ◽  
Transmission Lines ◽  
System Analysis ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Power System Analysis ◽  
Computational Performance ◽  
System Equations ◽  
The Time Domain

A new analysis method using wavelet domain for steady-state operating condition of power system is developed and introduced. Based on wavelet-Galerkin theory, the system components such as resistor, inductor, capacitor, transmission lines, and switching devices are modeled in discrete wavelet domain for the purpose of steady-state analysis. To solve system equations, they are transferred to wavelet domain by forming algebraic matrix-vector relations using the wavelet transform coefficients and the equivalent circuit is thus built for system simulation. After describing the new algorithm, two-case studies are presented and compared with the simulations in the time domain to verify the accuracy and computational performance.

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