Adaptive quantization using code length in image compression

• US 6,882,753 B2
• Filed: 06/04/2001
• Issued: 04/19/2005
• Est. Priority Date: 06/04/2001
• Status: Expired due to Term

• Current Assignee: Silicon Integrated Systems Corporation (Silicon Integrated Systems Corporation Taiwan)
• Original Assignee: Silicon Integrated Systems Corporation (Silicon Integrated Systems Corporation Taiwan)
• Inventors: Chen, Cheng-Hsien, Mei, Lin-Tien, Lee, Chen-Yi, Pai, Hung-Ta
• Primary Examiner(s): Mehta, Bhavesh M.
• Assistant Examiner(s): Bayat, Ali
• Application Number:
  US09/874,559
• Publication Number:
  US 20020181795A1
• Time in Patent Office: 1,415 Days
• Field of Search: 382/165, 382/166, 382/167, 382/251, 382/243, 382/250, 382/254, 382/232, 382/233, 382/239, 382/248, 382/270, 382/271, 382/272, 382/273, 382/246, 375/240.12, 375/240.24, 375/240.2, 375/240.15, 375/240, 375/240.3, 348/405, 358/1.15
• US Class Current: 382/251
• CPC Class Codes: G06T 9/007 Transform coding, e.g. discrete cosine transform
• CPC Class Codes: H04N 19/124 Quantisation
• CPC Class Codes: H04N 19/152 by measuring the fullness of the transmission buffer
• CPC Class Codes: H04N 19/17 the unit being an image region, e.g. an object
• CPC Class Codes: H04N 19/192 the adaptation method, adaptation tool or adaptation type being iterative or recursive
• CPC Class Codes: H04N 19/48 using compressed domain processing techniques other than decoding, e.g. modification of transform coefficients, variable length coding [VLC] data or run-length data motion estimation in a transform domain H04N19/547; processing of decoded motion vectors H04N19/513
• CPC Class Codes: H04N 19/60 using transform coding

Abstract

A method is adapted for compressing an image data block, and includes the steps of:

• • (a) subjecting the image data block to discrete cosine transformation so as to generate discrete cosine transform data;
  • (b) quantizing the discrete cosine transform data in accordance with a quantizer matrix that consists of an array of quantizing coefficients so as to generate quantized data;
  • (c) encoding the quantized data using an entropy coding algorithm so as to generate an encoded bitstream; and
  • (d) when the length of the encoded bitstream does not fall within a predetermined range, adjusting the quantizing coefficients in the quantizer matrix and repeating steps (b) and (c) until the length of the encoded bitstream falls within the predetermined range.

Claims

1. A method for compressing an image data block, comprising the steps of:

(a) subjecting the image data block to discrete cosine transformation so as to generate discrete cosine transform data;

(b) quantizing the discrete cosine transform data in accordance with a quantizer matrix that consists of an array of quantizing coefficients so as to generate quantized data, wherein each of the quantizing coefficients in the quantizer matrix is a power of 2;

(c) encoding the quantized data using an entropy coding algorithm so as to generate an encoded bitstream; and

(d) when the length of the encoded bitstream does not fall within a predetermined range, adjusting the quantizing coefficients in the quantizer matrix and repeating steps (b) and (c) until the length of the encoded bitstream falls within the predetermined range, wherein step (d) includes;

(d-1) grouping the quantizing coefficients in said quantizer matrix into a plurality of coefficient groups, the coefficient groups being arranged into lower-ordered groups that include a lowest-ordered group, and higher-ordered groups that include a highest-ordered group, the number of quantizing coefficients in each of the lower-ordered groups being less than that in each of the higher-ordered groups; and

(d-2) adjusting the quantizing coefficients in one of said coefficient groups according to the length of the encoded bitstream, wherein;

the quantizing coefficients are unscaled by a factor of 2 group-by-group starting from the highest-ordered group to the lowest-ordered group whenever the length of the encoded bitstream is greater than an upper limit of the predetermined range; and

the quantizing coefficients are downscaled by a factor of 2 group-by-group starting from the lowest-ordered group to the highest-ordered group whenever the length of the encoded bitstream is less than a lower limit of the predetermined range.

2. The method as claimed in claim 1, wherein the image data block is 2ⁿ×

2ⁿ in size, n being a positive integer.

3. The method as claimed in claim 2 wherein the image data block is one of Y, U and V color space image data blocks.

4. The method as claimed in claim 3 wherein the image data block is one of the U and V color space image data blocks, and is obtained by averaging adjacent discrete data in an initial image data block that is 2²⁺ⁿ×

2²⁺ⁿ in size to obtain the image data block that is 2ⁿ×

2ⁿ in size.

5. The method as claimed in claim 1, wherein the entropy coding algorithm is a variable length coding algorithm.

6. The method as claimed in claim 5 wherein the variable length coding algorithm is a Huffman coding algorithm.

7. A method for compressing an image data block, comprising the steps of:

(a) subjecting the image data block to discrete cosine transformation so as to generate discrete cosine transform data;

(b) quantizing the discrete cosine transform data in accordance with a quantizer matrix that consists of an array of quantizing coefficients so as to generate quantized data;

(c) encoding the quantized data using an entropy coding algorithm so as to generate an encoded bitstream; and

(d) when the length of the encoded bitstream does not fall within a predetermined range, adjusting the quantizing coefficients in the quantizer matrix and repeating steps (b) and (c) until the length of the encoded bitstream falls within the predetermined range;

wherein the image data block is 2ⁿ×

2ⁿ in size, n being a positive integer; and

wherein the image data block is one of the U and V color space image data blocks, and is obtained by averaging adjacent discrete data in an initial image data block that is 2²⁺ⁿ×

2²⁺ⁿ in size to obtain the image data block that is 2ⁿ×

2ⁿ in size.

8. The method as claimed in claim 7 wherein step (d) includes the sub-steps of:

(d-1) grouping the quantizing coefficients in said quantizer matrix into a plurality of coefficient groups; and

(d-2) adjusting the quantizing coefficients in one of said coefficient groups according to the length of the encoded bitstream.

9. The method as claimed in claim 8, wherein, in sub-step (d-1), the coefficient groups are arranged into lower-ordered groups that include a lowest-ordered group, and higher-ordered groups that include a highest-ordered group, the number of quantizing coefficients in each of the lower-ordered groups being less than that in each of the higher-ordered groups.

10. The method as claimed in claim 9, wherein each of the quantizing coefficients in the quantizer matrix is a power of 2.

11. The method as claimed in claim 10 wherein, in sub-step (d-2):

the quantizing coefficients are upscaled by a factor of 2 group-by-group starting from the highest-ordered group to the lowest-ordered group whenever the length of the encoded bitstream is greater than an upper limit of the predetermined range; and

the quantizing coefficients are downscaled by a factor of 2 group-by-group starting from the lowest-ordered group to the highest-ordered group whenever the length of the encoded bitstream is less than a lower limit of the predetermined range.

12. The method as claimed in claim 9 wherein the coefficient groups are obtained by dividing the quantizer matrix into diagonally extending sections.