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What is Wavelet

Chapter 9
Handbook of Research on Computational Forensics, Digital Crime, and Investigation: Methods and Solutions
Mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale.
Published in Chapter:
A Novel Multilevel DCT Based Reversible Data Hiding
Hong Cai (University of Texas at San Antonio, USA) and Sos S. Agaian (University of Texas at San Antonio, USA)
Copyright: © 2010 |Pages: 30
DOI: 10.4018/978-1-60566-836-9.ch009
Abstract
DCT and wavelet based techniques have been widely used in image processing, for example, the applications involving JPEG, MPEG and JPEG2000. To combine the advantages of DCT and wavelet, we introduce in this chapter a novel multilevel DCT decomposition method by exploiting the modified inverse Hilbert curve. The experimental results showed that the proposed multilevel decomposition can extract characteristic DCT coefficients and assign the coefficients to new neighborhoods with distinct frequency properties. We discuss a powerful reversible data hiding algorithm in JPEG images based on this new multilevel DCT. This lossless data hiding algorithm features a key-dependent (multilevel structure) coefficient-extension technique and an embedding location selector, and it can achieve high quality reconstructed images with disparate content types.
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Chapter 21
Interval Wavelet Method for Solving Imprecisely Defined Diffusion Equations
A wavelet may be defined as a wave-like oscillation with amplitude that begins at zero, increases, and then decreases back to zero, that is the value over the whole domain is zero.
Published in Chapter: Interval Wavelet Method for Solving Imprecisely Defined Diffusion Equations; From: Handbook of Research on Generalized and Hybrid Set Structures and Applications for Soft Computing
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Chapter 125
A Novel Blind Wavelet Base Watermarking of ECG Signals on Medical Images Using EZW Algorithm
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Chapter 627
Improved Wavelet Neural Networks and Its Applications in Function Approximation
A mathematical function that satisfies certain requirements, such as integrates to zero, oscillates and well localized in time.
Published in Chapter: Improved Wavelet Neural Networks and Its Applications in Function Approximation; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 29
Advanced ROI Coding Techniques for Medical Imaging
A one-dimensional pulse, usually the basic response from a single reflector. Its key attributes are its amplitude, frequency and phase. The wavelet originates as a packet of energy from the source point, having a specific origin in time, and is returned to the receivers as a series of events distributed in time and energy. The distribution is a function of velocity and density changes in the subsurface and the relative position of the source and receiver.
Published in Chapter: Advanced ROI Coding Techniques for Medical Imaging; From: Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
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