Hidden Bits In Wavelet Domain
A possible domain for watermark embedding is that of the wavelet domain. The Discrete Wavelet Transform separates an image into a lower resolution approximation image as well as horizontal, vertical and diagonal detail components. The process can then be repeated to computes multiple “scale” wavelet decomposition. One of the many advantages over the wavelet transform is that that it is believed to more accurately model aspects of the Human Visual System (HVS) as compared to the FFT or DCT. This allows us to use higher energy watermarks in regions that the HVS is known to be less sensitive to, such as the high resolution detail bands. Embedding watermarks in these regions allow us to increase the robustness of our watermark, at little to no additional impact on image quality. One of the most straightforward techniques is the embedding of a CDMA sequence in the detail bands. The wavelet domain as well proved to be highly resistant to both compression and noise, with minimal amounts of visual degradation. This is all the more impressive when one considers that the wavelet technique described here is one of the most primitive currently known. More sophisticated wavelet-domain techniques will almost certainly improve on both of these, and hopefully lower it’s computational requirements. The wavelet domain may be one of the most promising domains for digital watermarking yet found.
We have developed a new scheme for the embedding of watermark sequence with high capacity, using a multilevel approach for coefficients selection.
Index Terms: Matlab, source, code, wavelet, watermarking, capacity, human, visual, system, multilevel.
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Figure 1. Visible watermark |
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A simple and effective source code for High-Capacity Wavelet Based Watermarking. |
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Demo code (protected P-files) available for performance evaluation. Matlab Wavelet Toolbox is required. |
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Release
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Date
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Major features
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1.0
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2009.06.11 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. |
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High-Capacity Wavelet Based Watermarking. Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 100 EUROS (less than 140 U.S. Dollars).
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Once you have done this, please email us luigi.rosa@tiscali.it
As soon as possible (in a few days) you will receive our new release of High-Capacity Wavelet Based Watermarking. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership with The Mathworks. All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 2006a. Matlab Wavelet Toolbox is required. The code provided has to be considered “as is” and it is without any kind of warranty. The authors deny any kind of warranty concerning the code as well as any kind of responsibility for problems and damages which may be caused by the use of the code itself including all parts of the source code.
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A Numerical Tour of Signal Processing
Filed under: Computational Geometry, Image processing, Signal Processing, Tutorials
An interesting, full of pratical examples, tour of signal processing from Gabriel Peyré.
Introduction
Wavelet Processing
Approximation, Coding and Compression
Noise and Linear Denoising
Wavelet Non-linear Denoising
Variational Denoising
Variational Image Processing
Audio Processing
Higher Dimensional Signal Processing
Computer Graphics
Sparsity and Redundant Representations
Inverse Problems
Compressive Sensing
Numerical Analysis
Mesh Processing
Geodesic Processing
- Fast Marching in 2D
- Fast Marching in 3D
- Farthest Point Sampling
- Image Compression with Geodesic Triangulation
- Anisotropic Fast Marching
- Geodesic Computation on 3D Meshes
- Shape Matching using the Fast Marching
- Geodesic Surface Remeshing (soon available)
- Geodesic Bending Invariants (soon available)
- Heuristically Driven Propagation (soon available)
Popularity: 1% [?]
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