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transcript
Watermark Extraction Methods For Linearly Distorted Images to
Maximize Signal-to-Noise Ratio
Brandon MigdalBrandon MigdalMay 7May 7thth 2004 2004
Rochester Institute of TechnologyRochester Institute of TechnologyAdvisor: Dr. Carl SalvaggioAdvisor: Dr. Carl Salvaggio
OutlineOutline
Embedding ProcessEmbedding Process Research Research Extraction ProcessExtraction Process ResultsResults Future WorkFuture Work
Embedding ProcessEmbedding Process
Carrier Message
100101…
FFT
Multiplication
Inverse FFT
Scale AmplitudeZero Mean
Initial Image
FFT
+
Template DesignTemplate Design
ConsiderationsConsiderations Location DesignLocation Design ReasonsReasons
TemplateTemplate
TemplateTemplate
TemplateTemplate
Embedding ProcessEmbedding Process
Carrier Message
100101…
FFT
Multiplication
Inverse FFT
Scale AmplitudeZero Mean
Initial Image
FFT
+
CarrierCarrier
Carrier DesignCarrier Design
Random PhaseRandom Phase Generated Pseudo-Random Generated Pseudo-Random Scale based on Nyquist, and CSFScale based on Nyquist, and CSF Reasons Reasons
Embedded ImageEmbedded Image
Distortion Distortion
Research AreasResearch Areas
WindowingWindowing SubsettingSubsetting
WindowingWindowing
FFT
Windowing Technique
Substitute IntoLevel 3
Extraction Process
SubsettingSubsetting
Subset
Level 3Extraction Process
+
Extraction ProcessExtraction Process
Embedded Image
Level 3 Extraction
FFT FFT
Cross Correlation
FFT-1
Blurring Filter
SNR Extraction
Level 2 Extraction
Comparison
Image Information
Level 1 Extraction
Image Information
&SNR
Scaling Factor
X
+
Scaling Factor
X Divided by Total Number of Image Blocks
For All Image Blocks
Average Image Block
FFT
Cross Correlation
Binary Message
ResultsResults
SNR Ratios
5
10
15
20
25
30
35
0 2 4 6 8 10 12 14 16 18 20
Distortion
Sig
nal
-to
-No
ise Normal Whole
Hamming Whole
Hanning Whole
Expon. (Normal Whole)
Expon. (Hamming Whole)
Expon. (Hanning Whole)
ResultsResults
Improvement From Substeting Without Windowing
-0.00001
-0.000005
0
0.000005
0.00001
0.000015
0.00002
0 2 4 6 8 10 12 14 16 18 20
Distortion
Sig
nal
-to
-No
ise
SNR - SNR 4
SNR - SNR 16
Log. (SNR - SNR 16 )
Log. (SNR - SNR 4)
ResultsResults
Improvement From Subsetting With a Hanning Window
-1.50E-05
-1.00E-05
-5.00E-06
0.00E+00
5.00E-06
1.00E-05
1.50E-05
2.00E-05
2.50E-05
3.00E-05
3.50E-05
4.00E-05
0 2 4 6 8 10 12 14 16 18 20
Distortion
Sig
nal
-to
-No
ise
SNR - SNR 4
SNR - SNR 16
Log. (SNR - SNR 16 )
Log. (SNR - SNR 4)
ResultsResults
Improvements From Subsetting With a Hamming Window
-1.00E-05
-5.00E-06
0.00E+00
5.00E-06
1.00E-05
1.50E-05
2.00E-05
2.50E-05
3.00E-05
0 2 4 6 8 10 12 14 16 18 20
Distortion
Sig
nal
-to
-No
ise
SNR - SNR 4
SNR - SNR 16
Log. (SNR - SNR 4)
Log. (SNR - SNR 16 )
Future WorkFuture Work
WindowingWindowing SubsettingSubsetting
Reference MaterialReference Material Gonzalez, R., and R. Woods, Gonzalez, R., and R. Woods, Digital Image ProcessingDigital Image Processing, ,
Second Second Edition, 2002, New Jersey: Prentice HallEdition, 2002, New Jersey: Prentice Hall Rabbani, M., and C. Honsinger, Rabbani, M., and C. Honsinger, Data Embedding Using Data Embedding Using
Phase Phase DispersionDispersion, IEE Seminar , IEE Seminar on Secure on Secure Images and Image Images and Image Authentication Ref. No.00/039, Authentication Ref. No.00/039, 2000, Volume 5, 2000, Volume 5, pp. 1-7pp. 1-7
Xie, H. N. Hicksa, G. Kellera, H. Huangb, and V. Xie, H. N. Hicksa, G. Kellera, H. Huangb, and V. Kreinovich, Kreinovich, An IDL/ENVI implementation of the An IDL/ENVI implementation of the FFTbased algorithm for automatic image FFTbased algorithm for automatic image registrationregistration, Computers & Geosciences, 2003, , Computers & Geosciences, 2003, Volume Volume 29, pp. 1045–105529, pp. 1045–1055
Signal-to-Noise Calculations, January 2004, Signal-to-Noise Calculations, January 2004, http://emalwww.engin.umich.edu/emal/courses/SEM_lecthttp://emalwww.engin.umich.edu/emal/courses/SEM_lectureCureC W/SEM_SignalNoise.htmlW/SEM_SignalNoise.html
Questions?Questions?