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[WM]: Re: : Advantages of Wavelet watermarking
hi
spatial domain works directly on the pixels of the image....i.e u can manipulate the pixels of the image directly, while in
frequency domain u take the transform of the image and then manipulate it and again inverse transform it.
and abt ur other question...
watermarking can be done in any language ur comfortable with. but matlab contains many direct functions for which u will hav to
write long codes in other languages like C, java, vc++.
eg. matlab contains functions for reading image, all transforms like dct etc.... so the choice is urs....
hope u find it useful....
regards,
rajan
http://www.geocities.com/gwatermarker
--- "Srinivasan.R Rao" <sriramlogin@gmail.com> wrote:
> How does spatial domain,frequency domain works.
> Do any one of them have presentation or slides on watermarking.
> Is there any spacified language to develop watermarking.
>
> On 9/2/05, rajan sheth <rajansheth@yahoo.com> wrote:
> > this is wat i have understood and learnt from
> other group members....
> >
> > http://www.geocities.com/gwatermarker
> > (my site on watermarking)
> >
> >
>
**********************************DCT*********************************
> > Characteristic of DCT Coefficients
> > 1. Magnitude of DC component of an 8x8 block DCT
> > coefficient is
> > proportional to the average grey level of the
> corresponding block [Huang et
> > al. 2000].
> > 2. Provides excellent signal approximation with
> few
> > coefficients.
> > 3. Frequency components are ordered in a
> sequential
> > order, starting
> > with low frequency, mid frequency and high
> frequency components. Proper
> > components can be selected based on this.
> > 4. If most of the high frequency coefficients that
> are
> > zero then it
> > represents a smooth blocks [Jellinek 2000].
> > 5. If the low frequency AC coefficients have large
> > absolute values
> > they normally refer to an edge blocks [Jellinek
> 2000].
> > 6. It is faster and can be implemented in O (n log
> n)
> > operations
> >
> > Coefficient Selection Criteria
> > 1. Coefficients which have large perceptual
> capacity
> > should be
> > selected because they allow stronger watermarks to
> be embedded and result in
> > least perceptual distortion [Huang et al.
> > 2000].
> > 2. Those coefficients should be selected which are
> > least changed by
> > common image processing attacks like low-pass
> filtering, noise addition etc
> > [Huang et al. 2000].
> > 3. Low frequency AC components (or high value
> > coefficients) satisfy
> > the above criteria and are selected in most
> watermarking algorithms.
> > 4. Common image processing operation affects the
> high
> > frequency
> > components and hence it's not a good choice for
> watermarking.
> > 5. DC component can also be used because the
> magnitude
> > of DC
> > component is much larger than the AC component
> which means they have a very
> > high perceptual capacity. Secondly DC components
> are
> > less affected by common image processing attacks
> unlike AC component which
> > are very sensitive to such attacks [Huang et al.
> 2000].
> >
> >
> > Embedding in the transform domain by modifying the
> DCT coefficients offer
> > many advantages including robustness against
> unintentional
> > image processing attacks like brightness and
> contrast adjustment, gamma
> > correction, filtering, blurring etc. It also shows resistance
> > against compression. However most of
> the DCT based approaches do
> > not completely address the issue of geometric
> attacks
> > like cropping.
> > Nevertheless this
> > approach is much more robust compared to spatial
> domain approach.
> >
> >
> > As mentioned earlier using the transform domain
> for embedding watermarks
> > offers many advantages including robustness
> against
> > unintentional and unintentional attacks. Most of
> the DCT watermarking
> > algorithms show robustness against compression.
> This is
> > achieved by understanding and incorporating JPEG
> compression mechanism into
> > watermark embedder. Another advantage of using DCT
> for
> > watermarking is the extensive study of human
> visual system in this domain
> > which has resulted in the standard JPEG
> quantization
> > table. So watermarking can be more adaptive to HVS
> in this domain. However
> > most of the DCT based approaches do not completely address the issue
> > of geometric attacks like
> cropping and scaling.
> > Nevertheless this approach is much more robust
> compared to spatial
> > domain approach.
> >
> > ************************************
> > DWT***********************************
> >
> > Characteristics of DWT
> >
> > 1. The wavelet decomposition decomposes the image
> into
> > three
> > spatial directions i.e. horizontal, vertical and
> diagonal. Hence wavelets
> > reflect the anisotropic properties of HVS more
> precisely
> > [Voloshynovskiy et al. 2000].
> >
> > 2. Multi-resolution nature: Because of its
> > multi-resolution nature
> > they are suitable for applications which require
> scalability and tolerable
> > degradation. Hence it allows for progressive
> transmission
> > of images
> >
> > 3. The larger the magnitude of the wavelet
> coefficient
> > the more
> > significant it is.
> >
> > 4. Watermark detection at lower resolutions is
> > computationally
> > effective because at every successive resolution
> level there are few
> > frequency bands involved.
> >
> > 5. Multiresolution watermarking is robust against
> > downsampling
> > operation by a power of two in either space or
> time domain [Zhu 1999].
> >
> > 6. High resolution subbands helps to easily locate
> > edge and
> > textures patterns in an image.
> >
> > 7. Wavelet Transform is computationally efficient
> and
> > can be
> > implemented by using simple filter convolution.
> >
> > 8. Robustness: It is more robust against
> transmission
> > and decoding
> > errors.
> >
> > 9. Magnitude of DWT coefficients is larger in the
> > lowest bands (LL)
> > at each level of decomposition [Tao and Eskicioglu
> 2004].
> >
> > 10. Magnitude of DWT coefficients is smaller for
> other
> > bands (HH,
> > LH, HL).
> >
> > Coefficient Selection Criteria
> >
> > 1. According to Cox et al. and Huang et al. (2000)
> > watermark should
> > be embedded in the DC and the low frequency AC
> coefficients in the DCT
> > domain due to their large perceptual capacity.
> Similar
> > strategy can be applied to DWT as well by
> embedding in the LL4 subband.
> >
> > 2. Embedding watermark in the higher level
> subbands
> > increases the
> > robustness of the watermark however the image
> visual fidelity may be lost
> > which can be measured by PSNR.
> >
> > 3. Embedding the watermark in lower level subbands
> > increases the
>
=== message truncated ===
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