Lossy data compression exploiting distortion side information

• US 7,327,287 B2
• Filed: 12/07/2005
• Issued: 02/05/2008
• Est. Priority Date: 12/09/2004
• Status: Expired due to Fees

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Martinian, Emin, Wornell, Gregory W., Zamir, Ram
• Primary Examiner(s): Williams; Howard L.
• Application Number:
  US11/296,649
• Publication Number:
  US 20060170571A1
• Time in Patent Office: 790 Days
• Field of Search: 341/51, 341/87, 382/239, 382/248, 382251-253, 375/240.02, 704/200.1
• US Class Current: 341/51
• CPC Class Codes: H03M 7/30 Compression speech analysis-synthesis for redundancy reduction G10L19/00; for image communication H04N; Expansion; Suppression of unnecessary data, e.g. redundancy reduction

Abstract

Described are techniques for performing lossy encoding. Source data and quality data are received by an encoder. The encoder maps the source data into a compressed representation having a level of distortion in accordance with the quality information. The compressed representation may be decoded without using the quality information.

Claims

1. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data including a plurality of components having a first representation into a compressed representation in which each of said plurality of components has an associated level of distortion in the compressed representation determined in accordance with a value of said each component relative to others of said plurality of components as indicated in the quality information, wherein said compressed representation may be decoded without knowledge of said quality information.

2. The method of claim 1, wherein the compressed representation is formed using a fixed codebook with a variable partition.

3. The method of claim 1, wherein the compressed representation is formed using a transform.

4. The method of claim 1, wherein said quality information indicates an importance of each of said plurality of components included in said source data relative to other components included in said source data.

5. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the quality information includes a distortion weighting value for each source sample included in said source data, said weighting value weighting an error between said each source sample and a lossy reconstruction of said source sample.

6. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the compressed representation is formed using a lattice.

7. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the compressed representation is formed using nested lattices.

8. A method for performing lossy encoding comprising:

receiving source data and cuality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the compressed representation is formed using a curve fitting technique.

9. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the compressed representation is formed using an error correcting code.

10. A method for performing lossy encoding comprising:

receiving source data and quality information; and

mapping the source data into a compressed representation having a level of distortion in accordance with the quality information, wherein said compressed representation may be decoded without using said quality information, wherein the compressed representation is formed using a hierarchy of one or more lattices and a linear code.

11. The method of claim 10, wherein a first source sample included in said source data is indicated by said quality information as more important than a second source sample included in said source data, and said first source sample is assigned a first lattice in said hierarchy and said second source sample is assigned a second different lattice in said hierarchy.

12. The method of claim 11, further comprising:

determining a quantization point in a lattice assigned to a source sample included in said source data; and

decomposing said quantization point for said source sample in said source data in accordance with quality information for said source sample.

13. The method of claim 12, wherein said decomposing further comprises:

performing a number of iterations of a decomposition step in accordance with a specified level of quality information for said source sample.

14. The method of claim 11, further comprising:

quantizing all source samples of said source data of a certain quality level as indicated by the quality data in accordance with an assigned lattice of quantization points;

decomposing each source sample of said certain quality level into one or more decomposition components; and

performing a first technique to correctly match a first decomposition component of each source sample of said certain quality level.

15. The method of claim 14, wherein said first technique interpolates a decomposition component for another source sample at a quality level other than said certain quality level.

16. A method for performing lossy encoding comprising:

receiving a set of points and a set of quality information; and

mapping said set of points to quantized points, wherein a first rule is used for mapping a first of said points to a first quantized point in accordance with a fixed codebook and a first indicator in said quality information, said first indicator indicating a value of said first point relative to other points in said set, said first rule resulting in a level of distortion introduced by said mapping in accordance with said value associated with said first point, a second rule is used for mapping a second of said points to a second quantized point in accordance with said codebook and a second indicator in said quality information, said second indicator indicating a value of said second point relative to other points in said set, said second rule resulting in a level of distortion introduced by said mapping in accordance with said value associated with said second point.

17. The method of claim 16, wherein said quality information indicates an importance of each point in said set of points relative to other points included in said set of points.

18. The method of claim 17, wherein a rule is associated with each level of quality indicated in said quality information, said rule being used to determine a partition associated with each quantization point in said fixed codebook, said partition varying in accordance with said each level of quality.

19. The method of claim 18, wherein a first rule defines a quality level indicating that said first point is more important than said second point, said first rule defining partitions having a finer granularity than partitions defined by said second rule.

20. A method for performing lossy encoding comprising:

receiving a fixed codebook of quantization points and a plurality of rules, each rule defining a different partition used in mapping a source point to a quantization point;

receiving source data including a plurality of source points;

receiving quality information indicating a plurality of quality levels, each of said quality levels being associated with a different one of said rules, each of said source points being associated with one of said plurality of quality levels; and

determining a quantization point for each of said source points in accordance with a quality level and associated rule for each source point.

21. A computer readable medium comprising code stored thereon for performing lossy encoding, the computer readable medium comprising code stored thereon for:

receiving source data and quality information; and

mapping the source data including a plurality of components having a first representation into a compressed representation in which each of said plurality of components has an associated level of distortion in the compressed representation determined in accordance with a value of said each component relative to others of said plurality of components as indicated in the quality information, wherein said compressed representation may be decoded without knowledge of said quality information.

22. The computer readable medium of claim 21, wherein the compressed representation is formed using a fixed codebook with a variable partition.

23. The computer readable medium of claim 21, wherein the quality information includes a distortion weighting value for each component included in said source data, said weighting value weighting an error between said each component and a lossy reconstruction of said each component.

24. The computer readable medium of claim 21, wherein the compressed representation is formed using a lattice.

25. The computer readable medium of claim 21, wherein the compressed representation is formed using nested lattices.

26. The computer readable medium of claim 21, wherein the compressed representation is formed using a transform.

27. The computer readable medium of claim 21, wherein the compressed representation is formed using a curve fitting technique.

28. The computer readable medium of claim 21, wherein the compressed representation is formed using an error correcting code.

29. The computer readable medium of claim 21, wherein the compressed representation is formed using a hierarchy of one or more lattices and a linear code.

30. The computer readable medium of claim 29, wherein a first component included in said source data is indicated by said quality information as more important than a second component included in said source data, and said first component is assigned a first lattice in said hierarchy and said second component is assigned a second different lattice in said hierarchy.

31. The computer readable medium of claim 30, further comprising code for:

determining a quantization point in a lattice assigned to a component included in said source data; and

decomposing said quantization point for said component in said source data in accordance with quality information for said component.

32. The computer readable medium of claim 31, wherein said code for decomposing further comprises code for:

performing a number of iterations of a decomposition step in accordance with a specified level of quality information for said component.

33. The computer readable medium of claim 30, further comprising code for:

quantizing all components of said source data of a certain quality level as indicated by the quality data in accordance with an assigned lattice of quantization points;

decomposing each component of said certain quality level into one or more decomposition components; and

performing a first technique to correctly match a first decomposition component of each component of said certain quality level.

34. The computer readable medium of claim 33, wherein said first technique interpolates a decomposition component for another component at a quality level other than said certain quality level.

35. The computer readable medium of claim 21, wherein said quality information indicates an importance of each component included in said source data relative to other components included in said source data.

36. A computer readable medium comprising code stored thereon for performing lossy encoding, the computer readable medium comprising code stored thereon for:

receiving a set of points and a set of quality information; and

mapping said set of points to quantized points, wherein a first rule is used for mapping a first of said points to a first quantized point in accordance with a fixed codebook and a first indicator in said quality information, said first indicator indicating a value of said first point relative to other points in said set, said first rule resulting in a level of distortion introduced by said mapping in accordance with said value associated with said first point, a second rule is used for mapping a second of said points to a second quantized point in accordance with said codebook and a second indicator in said quality information, said second indicator indicating a value of said second point relative to other points in said set, said second rule resulting in a level of distortion introduced by said mapping in accordance with said value associated with said second point.

37. The computer readable medium of claim 36, wherein said quality information indicates an importance of each point in said set of points relative to other points included in said set of points.

38. The computer readable medium of claim 37, wherein a rule is associated with each level of quality indicated in said quality information, said rule being used to determine a partition associated with each quantization point in said fixed codebook, said partition varying in accordance with said each level of quality.

39. The computer readable medium of claim 38, wherein a first rule defines a quality level indicating that said first point is more important than said second point, said first rule defining partitions having a finer granularity than partitions defined by said second rule.

40. A computer readable medium comprising code stored thereon for performing lossy encoding, the computer readable medium comprising code stored thereon for:

receiving a fixed codebook of quantization points and a plurality of rules, each rule defining a different partition used in mapping a source point to a quantization point;

receiving source data including a plurality of source points,

receiving quality information indicating a plurality of quality levels, each of said quality levels being associated with a different one of said rules, each of said source points being associated with one of said plurality of quality levels; and

determining a quantization point for each of said source points in accordance with a quality level and associated rule for each source point.