WYNER-ZIV SUCCESSIVE REFINEMENT VIDEO COMPRESSION

• US 20090003452A1
• Filed: 06/26/2008
• Published: 01/01/2009
• Est. Priority Date: 06/29/2007
• Status: Abandoned Application

• Current Assignee: Pai Kung LLC (Intellectual Ventures LLC)
• Original Assignee: Hong Kong University of Science and Technology
• Inventors: Au, Oscar Chi Lim, Fan, Xiaopeng
• Application Number:
  US12/147,457
• Publication Number:
  US 20090003452A1
• Time in Patent Office: Days
• US Class Current: 375/240.170
• CPC Class Codes: H04N 19/395 involving distributed video coding [DVC], e.g. Wyner-Ziv video coding or Slepian-Wolf video coding
• CPC Class Codes: H04N 19/53 Multi-resolution motion estimation; Hierarchical motion estimation

Abstract

Improved methods, systems, and devices for Wyner-Ziv video compression are provided based on the disclosed successive resolution refinement techniques. The disclosed resolution refinement schemes improve rate-distortion performance, visual quality and decoding speed with lower complexity than conventional bitplane refinement methods. The disclosed details enable various refinements and modifications according to system design considerations.

Claims

1. A method for coding and decoding a video sequence having a plurality of frames, comprising:

quantizing a first frame of the plurality of frames into a plurality of binaries;

partitioning the plurality of binaries into at least a base layer bin and an enhance layer bin;

compressing and transmitting the base layer bin and the enhance layer bin to a decoder;

decoding the base layer bin at the decoder using a first prediction frame to create a base layer reconstruction;

performing a motion estimation using the base layer reconstruction to determine a second prediction frame, the second prediction frame provides a more accurate motion estimation than the first prediction frame; and

decoding the enhance layer bin using the second prediction frame to create a refined frame reconstruction.

2. The method of claim 1, the quantizing includes quantizing according to an N-Queen pattern.

3. The method of claim 2, the quantizing includes quantizing using a quantization step having a value of one of 32 and 64.

4. The method of claim 1, the compressing includes coding according to a Slepian-Wolf Codec.

5. The method of claim 1, the decoding the base layer bin at the decoder using a first prediction frame includes using a prediction frame based at least in part on one of a motion compensated extrapolation result or a motion compensated interpolation result.

6. The method of claim 1, the performing a motion estimation using the base layer reconstruction includes using the base layer reconstruction as a block matching target.

7. The method of claim 1, the quantizing includes dithered quantizing.

8. The method of claim 1, further comprising:

using a low-pass filter to remove contours in the refined frame reconstruction.

9. The method of claim 1, further comprising:

performing a motion compensated refinement at the decoder after all bins are decoded to improve the quality of the refined frame reconstruction.

10. A computer readable medium comprising computer executable instructions for performing the method of claim 1.

11. A computing device comprising means for performing the method of claim 1.

12. A method for decoding a video stream having a plurality of video stream frames, comprising:

receiving at least one of the plurality of video stream frames;

processing the at least one of the plurality of video stream frames by a n-stage decoder component, where n is an integer, the processing further comprising;

dividing each received frame into n layers comprising higher and lower layers; and

successively reconstructing the n layers in the n-stage decoder component using lower layer reconstruction to refine motion vectors and side information in successively higher layer reconstruction.

13. The method of claim 12, the processing includes processing substantially in the pixel domain.

14. The method of claim 12, the processing includes processing substantially in the transform domain.

15. The method of claim 12, the processing further includes applying a low-pass filter after successively reconstructing the n layers.

16. The method of claim 12, the receiving includes receiving the at least one of the plurality of video stream frames over a network.

17. The method of claim 12, the receiving includes receiving the at least one of the plurality of video stream frames from a local data store.

18. A video compression system, comprising:

an application component that requests decoding of a plurality of frames of video data; and

a processing component for processing the plurality of frames in response to the request, the processing component further comprising;

a multi-stage decoder component that successively reconstructs each layer of a divided frame using a lower layer reconstruction to provide refined motion vectors and refined current frame information for higher layer reconstruction.

19. The system of claim 18, further comprising a multi-stage encoder component for dividing each frame of the plurality of frames into higher and lower layers;

20. The system of claim 18, further comprising at least one of a low-pass filter component that removes contours in a refined current frame and motion compensation refinement component that improves the quality of the refined current frame.