Quantization-based data embedding in mapped data
Novel methods and systems for quantization based data embedding and reading in host signals, such as image, audio and video signals. To embed auxiliary data in a host signal, an embedder maps the host signal from a first domain into a mapped signal in a second domain. The embedder performs quantization based embedding of auxiliary data into the host signal using quantizers. The quantizers are adapted such that the relationship between corresponding quantizers in the first and second domains satisfies a predetermined constraint. The mapping improves the robustness of the data embedding method by increasing the chances that the embedded data can be recovered by an auxiliary data reader after modifications. A related embedding method projects the mapped signal unto a vector, and specifically, a pseudorandom vector. It performs quantization based embedding on the projected signal. The use of this projection provides added robustness of the embedded data to noise and other forms of distortion.
1. A method comprising:
reading an electronic host media signal from a memory;
mapping the electronic host media signal from a first domain to a second domain;
computing quantization bins in the first and second domains, wherein the quantization bins satisfy a constraint, and wherein the mapping identifies corresponding quantization bins in the first and second domains; and
embedding auxiliary data into the electronic host media signal using the quantization bins from the second domain, wherein the embedding comprises quantization-based embedding.
2. The method of claim 1 , wherein mapping the electronic host media signal comprises computing a cumulative distribution function of the electronic host media signal.
3. The method of claim 1 , wherein the quantization based embedding further comprises embedding the auxiliary data by adjusting values of the electronic host media signal, and wherein the adjusted values fall into bins corresponding to auxiliary data symbols to be embedded.
4. The method of claim 3 , wherein spacing of the bins is at least initially uniform in the second domain, and is non-uniform in the first domain.
5. The method of claim 3 , further comprising adapting spacing of the bins in the first domain to make the spacing more uniform in the first domain.
6. The method of claim 3 , further comprising assigning the bins using a finite state machine.
7. The method of claim 5 , further comprising embedding a reference signal comprising known auxiliary data values for use in deriving bin arrangement in an auxiliary data reader.
8. A method comprising:
mapping an electronic host media signal from a first domain to a second domain;
projecting the mapped signal onto a pseudo random vector;
computing quantizers in the first and second domains, wherein the quantizers in the first and second domains satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
performing a quantization based embedding on the projection of the mapped signal onto the pseudo random vector.
9. The method of claim 8 , further comprising:
partitioning the electronic host media signal into vectors of elements; and
projecting each vector onto a corresponding pseudorandom vector.
10. The method of claim 9 , further comprising selecting the vectors of elements from pseudorandom locations in the electronic host media signal.
11. The method of claim 8 , further comprising performing a weighted projection onto the pseudorandom vector.
12. The method of claim 11 , wherein performing a weighted projection further comprises deriving weights used in the weighted projection from the electronic host media signal to increase at least one of robustness of the embedded data or perceptual quality of the electronic host media signal after embedding.
13. The method of claim 11 , wherein performing a weighted projection further comprises computing weights used in the weighted projection, wherein the weights are derivable from the electronic host media signal after embedding and distortion of the electronic host media signal.
14. The method of claim 11 , further comprising embedding a reference signal comprising known auxiliary values for use in deriving the weights in an auxiliary data reader for reading the embedded data from the electronic host media signal.
15. A non-transitory computer readable medium having instructions stored thereon, the instructions comprising:
instructions to read an electronic host media signal from a memory;
instructions to map the electronic host media signal from a first domain to a second domain;
instructions to compute quantization bins in the first and second domains, wherein the quantization bins satisfy a constraint, and wherein the mapping identifies corresponding quantization bins in the first and second domains; and
instructions to embed auxiliary data into the electronic host media signal using the quantization bins from the second domain, wherein the embedding comprises quantization-based embedding.
16. A non-transitory computer readable medium having instructions stored thereon, the instructions comprising:
instructions to map an electronic host media signal from a first domain to a second domain;
instructions to project the mapped signal onto a pseudo random vector;
instructions to compute quantizers in the first and second domains, wherein the quantizers in the first and second domains satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
instructions to perform a quantization based embedding on the projection of the mapped signal onto the pseudo random vector.
17. A method comprising:
mapping an electronic host media signal from a first domain to a second domain that is robust to a class of modifications;
computing quantizers in the first and second domains, wherein the quantizers in the first and second domains satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
reading auxiliary data embedded into the electronic host media signal using quantizers computed from the second domain, wherein the reading comprises quantization-based reading.
18. The method of claim 17 , further comprising deriving the quantizers using reference signal values embedded into the electronic host media signal.
19. The method of claim 18 , wherein the reference signal values comprise training data embedded using quantization-based embedding.
20. The method of claim 17 , further comprising predicting the quantizers using dynamic programming.
21. The method of claim 17 , further comprising predicting the quantizers using a structured search through possible state transitions.
22. The method of claim 21 , further comprising predicting the quantizers using a Viterbi method.
23. A non-transitory computer readable medium having instructions stored thereon, the instructions comprising:
instructions to map an electronic host media signal from a first domain to a second domain that is robust to a class of modifications;
instructions to compute quantizers in the first and second domains, wherein the quantizers in the first and second domains satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
instructions to read auxiliary data embedded into the electronic host media signal using quantizers computed from the second domain, wherein the reading comprises quantization-based reading.
24. A method comprising:
mapping an electronic host media signal from a first domain to a second domain that is robust to a class of modifications;
projecting the mapped signal onto a pseudo random vector;
computing quantizers in the first and second domains, wherein the quantizers satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
reading auxiliary data embedded in a projection of the mapped signal onto the pseudo random vector, wherein the reading comprises quantization-based reading.
25. The method of claim 24 , further comprising:
partitioning the electronic host media signal into vectors of elements; and
projecting each vector onto a corresponding pseudorandom vector.
26. The method of claim 25 , further comprising selecting the vectors of elements from pseudorandom locations in the electronic host media signal.
27. The method of claim 24 , further comprising performing a weighted projection onto the pseudorandom vector.
28. The method of claim 27 , wherein performing a weighted projection further comprises deriving weights used in the weighted projection from the electronic host media signal to increase at least one of robustness of the embedded data or perceptual quality of the electronic host media signal after embedding.
29. The method of claim 27 , wherein performing a weighted projection further comprises computing weights used in the weighted projection, wherein the weights are derivable from the electronic host media signal after embedding and distortion of the electronic host media signal.
30. The method of claim 27 , further comprising reading an embedded reference signal comprising known auxiliary values to derive the weights.
31. A non-transitory computer readable medium having instructions stored thereon, the instructions comprising:
instructions to map the electronic host media signal from a first domain to a second domain that is robust to a class of modifications;
instructions to project the mapped signal onto a pseudo random vector;
instructions to compute quantizers in the first and second domains, wherein the quantizers satisfy a constraint, and wherein the mapping identifies corresponding quantizers in the first and second domains; and
instructions to read auxiliary data embedded in a projection of the mapped signal onto the pseudo random vector, wherein the reading comprises quantization-based reading.