Methods and apparatus for video size conversion

• US 7,676,106 B2
• Filed: 07/03/2003
• Issued: 03/09/2010
• Est. Priority Date: 06/09/2000
• Status: Active Grant

• Current Assignee: Google Technology Holdings LLC (Alphabet Inc.)
• Original Assignee: General Instrument Corporation (CommScope Holding Company, Inc.)
• Inventors: Panusopone, Krit, Chen, Xuemin
• Primary Examiner(s): Tran; Phuoc
• Application Number:
  US10/613,865
• Publication Number:
  US 20040013195A1
• Time in Patent Office: 2,441 Days
• Field of Search: 382/250, 382/235, 382/264, 382/299, 708/402, 375/240.2
• US Class Current: 382/250
• CPC Class Codes: H04N 19/105 Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
• CPC Class Codes: H04N 19/112 according to a given display mode, e.g. for interlaced or progressive display mode
• CPC Class Codes: H04N 19/132 Sampling, masking or truncation of coding units, e.g. adaptive resampling, frame skipping, frame interpolation or high-frequency transform coefficient masking
• CPC Class Codes: H04N 19/137 Motion inside a coding unit, e.g. average field, frame or block difference
• CPC Class Codes: H04N 19/196 being specially adapted for the computation of encoding parameters, e.g. by averaging previously computed encoding parameters processing of motion vectors H04N19/513
• CPC Class Codes: H04N 19/198 including smoothing of a sequence of encoding parameters, e.g. by averaging, by choice of the maximum, minimum or median value
• CPC Class Codes: H04N 19/20 using video object coding
• CPC Class Codes: H04N 19/40 using video transcoding, i.e. partial or full decoding of a coded input stream followed by re-encoding of the decoded output stream
• CPC Class Codes: H04N 19/59 involving spatial sub-sampling or interpolation, e.g. alteration of picture size or resolution
• CPC Class Codes: H04N 19/70 characterised by syntax aspects related to video coding, e.g. related to compression standards
• CPC Class Codes: H04N 21/234309 by transcoding between formats or standards, e.g. from MPEG-2 to MPEG-4 or from Quicktime to Realvideo conversion of standards in analog television systems H04N7/01
• CPC Class Codes: H04N 21/23439 for generating different versions
• CPC Class Codes: H04N 21/23608 Remultiplexing multiplex streams, e.g. involving modifying time stamps or remapping the packet identifiers

Abstract

Methods and apparatus for performing 2:1 downscaling on video data are provided. At least one input matrix of N×N (e.g., N=16) Discrete Cosine Transform (DCT) coefficients is formed from the video data by combining four N/2×N/2 field-mode DCT blocks. Vertical downsampling and de-interlacing are performed to the input matrix to obtain two N/2×N/2 frame-mode DCT blocks. An N×N/2 input matrix is formed from the two frame-mode DCT blocks. Horizontal downsampling is performed to the N×N/2 matrix to obtain one N/2×N/2 frame-mode DCT block.

Claims

1. A method for performing 2:

1 downscaling on video data, comprising the steps of;

forming at least one input matrix of N×

N Discrete Cosine Transform (DCT) coefficients from the video data by combining four N/2×

N/2 field-mode DCT blocks;

performing vertical downsampling and de-interlacing to the input matrix to obtain two N/2×

N/2 frame-mode DCT blocks;

forming an N×

N/2 input matrix from the two frame-mode DCT blocks; and

performing horizontal downsampling to the N×

N/2 matrix to obtain one N/2×

N/2 frame-mode DCT block.

2. The method of claim 1, wherein N=16.

3. The method of claim 1, wherein:

the vertical downsampling also achieves low pass filtering of the N×

N input matrix.

4. The method of claim 1, wherein:

the vertical downsampling uses a sparse downsampling matrix.

5. The method of claim 4, wherein:

the sparse downsampling matrix=0.5[I₈ I₈], where I₈ is an 8×

8 identity matrix.

6. The method of claim 1, wherein:

the horizontal downsampling uses a sparse downsampling matrix composed of odd “

O” and

even “

E”

matrices.

7. The method of claim 6, wherein:

the even matrix has the following form;

$E=\left[\begin{array}{cccc}e<br><br>\left(0\right)& 0& 0& 0,\\ 0& e<br><br>\left(1\right)& 0& e<br><br>\left(2\right),\\ 0& 0& 0& 0,\\ 0& e<br><br>\left(3\right)& 0& e<br><br>\left(4\right),\\ 0& 0& e<br><br>\left(5\right)& 0,\\ 0& e<br><br>\left(6\right)& 0& e<br><br>\left(7\right),\\ 0& 0& 0& 0,\\ 0& e<br><br>\left(8\right)& 0& e<br><br>\left(9\right)\end{array}\right]$

where e(1) through e(9) are non-zero coefficients; and

the odd matrix has the following form;

$O=\left[\begin{array}{cccc}0& 0& 0& 0,\\ o<br><br>\left(0\right)& 0& o<br><br>\left(1\right)& 0,\\ 0& o<br><br>\left(2\right)& 0& 0,\\ o<br><br>\left(3\right)& 0& o<br><br>\left(4\right)& 0,\\ 0& 0& 0& 0,\\ o<br><br>\left(5\right)& 0& o<br><br>\left(6\right)& 0,\\ 0& 0& 0& o<br><br>\left(7\right),\\ o<br><br>\left(8\right)& 0& o<br><br>\left(9\right)& 0\end{array}\right]$

where o(1) through o(9) are non-zero coefficients.

8. An apparatus for performing 2:

1 downscaling on video data, comprising;

means for forming at least one input matrix of N×

N Discrete Cosine Transform (DCT) coefficients from the video data by combining four N/2×

N/2 field-mode DCT blocks;

means for performing vertical downsampling and de-interlacing to the input matrix to obtain two N/2×

N/2 frame-mode DCT blocks;

means for forming an N×

N/2 input matrix from the two frame-mode DCT blocks; and

means for performing horizontal downsampling to the N×

N/2 matrix to obtain one N/2×

N/2 frame-mode DCT block.

9. The apparatus of claim 8, wherein N=16.

10. The apparatus of claim 8, wherein:

the means for performing vertical downsampling also achieves low pass. filtering of the N×

N input matrix.

11. The apparatus of claim 8, wherein:

the means for performing vertical downsampling uses a sparse downsampling matrix.

12. The apparatus of claim 11, wherein:

the sparse downsampling matrix=0.5[I₈ I₈], where I₈ is an 8×

8 identity matrix.

13. The apparatus of claim 8, wherein:

the means for performing horizontal downsampling uses a sparse downsampling matrix composed of odd “

O” and

even “

E”

matrices.

14. The apparatus of claim 13, wherein:

the even matrix has the following form;

$E=\left[\begin{array}{cccc}e<br><br>\left(0\right)& 0& 0& 0,\\ 0& e<br><br>\left(1\right)& 0& e<br><br>\left(2\right),\\ 0& 0& 0& 0,\\ 0& e<br><br>\left(3\right)& 0& e<br><br>\left(4\right),\\ 0& 0& e<br><br>\left(5\right)& 0,\\ 0& e<br><br>\left(6\right)& 0& e<br><br>\left(7\right),\\ 0& 0& 0& 0,\\ 0& e<br><br>\left(8\right)& 0& e<br><br>\left(9\right)\end{array}\right]$

where e(1) through e(9) are non-zero coefficients; and

the odd matrix has the following form;

$O=\left[\begin{array}{cccc}0& 0& 0& 0,\\ o<br><br>\left(0\right)& 0& o<br><br>\left(1\right)& 0,\\ 0& o<br><br>\left(2\right)& 0& 0,\\ o<br><br>\left(3\right)& 0& o<br><br>\left(4\right)& 0,\\ 0& 0& 0& 0,\\ o<br><br>\left(5\right)& 0& o<br><br>\left(6\right)& 0,\\ 0& 0& 0& o<br><br>\left(7\right),\\ o<br><br>\left(8\right)& 0& o<br><br>\left(9\right)& 0\end{array}\right]$

where o(1) through o(9) are non-zero coefficients.