Quantization table adjustment

• US 6,553,142 B2
• Filed: 07/17/2002
• Issued: 04/22/2003
• Est. Priority Date: 12/13/1991
• Status: Expired due to Fees

• Current Assignee: Avid Technology Incorporated
• Original Assignee: Avid Technology Incorporated
• Inventors: Peters, Eric C.
• Primary Examiner(s): Couso; Jose L.
• Application Number:
  US10/197,682
• Publication Number:
  US 20030002741A1
• Time in Patent Office: 279 Days
• Field of Search: 382/232,233,234,250,251,254,276,279 348/403.1,405.1 358/432,433
• US Class Current: 382/232
• CPC Class Codes: G06F 3/0219 Special purpose keyboards
• CPC Class Codes: G06F 3/0362 with detection of 1D translations or rotations of an operating part of the device, e.g. scroll wheels, sliders, knobs, rollers or belts
• CPC Class Codes: G06F 3/038 Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
• CPC Class Codes: G06F 3/0489 using dedicated keyboard keys or combinations thereof
• CPC Class Codes: G06F 5/06 for changing the speed of data flow, i.e. speed regularising or timing, e.g. delay lines, FIFO buffers; over- or underrun control therefor G06F7/78 takes precedence
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G11B 27/034 on discs G11B27/036, G11B27/038 take precedence
• CPC Class Codes: G11B 27/28 by using information signals recorded by the same method as the main recording G11B27/22 takes precedence
• CPC Class Codes: G11B 27/34 Indicating arrangements indicating means incorporated in magazine or cassette G11B23/046 and G11B23/0875; indicating measured values in general G01D
• CPC Class Codes: H04N 19/115 Selection of the code volume for a coding unit prior to coding
• CPC Class Codes: H04N 19/124 Quantisation
• CPC Class Codes: H04N 19/126 Details of normalisation or weighting functions, e.g. normalisation matrices or variable uniform quantisers
• CPC Class Codes: H04N 19/146 Data rate or code amount at the encoder output
• CPC Class Codes: H04N 19/149 by estimating the code amount by means of a model, e.g. mathematical model or statistical model
• CPC Class Codes: H04N 19/15 by monitoring actual compressed data size at the memory before deciding storage at the transmission buffer
• CPC Class Codes: H04N 19/154 Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion use of rate-distortion criteria H04N19/147
• CPC Class Codes: H04N 19/162 User input
• CPC Class Codes: H04N 19/176 the region being a block, e.g. a macroblock
• CPC Class Codes: H04N 19/18 the unit being a set of transform coefficients
• CPC Class Codes: H04N 19/42 characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation H04N19/635 takes precedence
• CPC Class Codes: H04N 19/60 : using transform coding
• CPC Class Codes: H04N 5/85 : on discs or drums
• CPC Class Codes: H04N 5/907 : using static stores, e.g. storage tubes or semiconductor memories H04N5/91 takes precedence
• CPC Class Codes: H04N 5/9264 : using transform coding
• CPC Class Codes: H04N 7/24 : Systems for the transmission of television signals using pulse code modulation H04N21/00 takes precedence
• CPC Class Codes: H04N 9/8042 : involving data reduction

Abstract

The method for adjusting quality during image capture includes computing a discrete cosine transform of a digital image to create DCT coefficients. A quantization table is generated that specifies frequency bands to be filtered and the DCT coefficients are digitized using the quantization table. It is preferred that the DCT coefficients be ordered in a zig-zag sequence to facilitate run-length encoding.

Claims

1. A method for compressing image data, comprising:

receiving the image data,

transforming a block of the image data using a discrete cosine transform to obtain a matrix of coefficients, wherein each coefficient corresponds to a frequency in a range of frequencies having low frequencies and high frequencies;

defining at least one quantization matrix, wherein the quantization matrix has a plurality of quantization values, wherein each quantization value corresponds to a coefficient in the matrix of coefficients, and wherein each quantization value corresponds to a frequency in the range of frequencies having low frequencies and high frequencies, wherein the quantization values are defined to obtain a desired amount of data from processing the matrix of coefficients, wherein the quantization values in different quantization matrices are such that for increased compression, a quantization value corresponding to at least one higher frequency is changed whereas quantization values corresponding to at least one lower frequency is unchanged;

quantizing the coefficients for the block of the image data using the defined quantization matrix; and

encoding the quantized coefficients to produce compressed image data.

2. The method of claim 1, wherein for further compression, high frequency components above a cut-off frequency are filtered out by the quantization matrix.

3. The method of claim 2, further comprising:

comparing an amount of data obtained from the encoding to a target amount of data; and

adjusting the cutoff frequency to increase compression if the amount of data is greater than the target amount.

4. The method of claim 3, wherein the quantization matrix is defined such that quantization values below but near the cut-off frequency are changed to mute the corresponding frequency components.

5. The method of claim 2, wherein the quantization matrix is defined such that quantization values below but near the cut-off frequency are changed to mute the corresponding frequency components.

6. The method of claim 1, further comprising:

comparing an amount of data obtained from the encoding to a target amount of data; and

adjusting the quantization matrix to increase compression by changing a quantization value corresponding to at least one higher frequency whereas quantization values corresponding to lower frequencies are unchanged.

7. The method of claim 1, wherein quantization values are larger for high frequencies than for low frequencies.

8. The method of claim 1, wherein quantization values increase from low frequencies to high frequencies.

9. The method of claim 1, wherein quantization values increase from low frequencies to a cutoff frequency, and wherein quantization values corresponding to frequencies above the cutoff frequency are a maximum value.

10. The method of claim 1, further comprising storing the compressed image data in a data file.

11. The method of claim 1, further comprising decompressing the compressed image data.

12. The method of claim 11, wherein decompressing comprises:

decoding the compressed image data to produce a set of coefficients; and

performing an inverse transform on the set of coefficients to generate image data.

13. An apparatus for compressing image data, comprising:

means for transforming a block of the image data using a discrete cosine transform to obtain a matrix of coefficients, wherein each coefficient corresponds to a frequency in a range of frequencies having low frequencies and high frequencies;

means for specifying at least one quantization matrix, wherein the quantization matrix has a plurality of quantization values, wherein each quantization value corresponds to a coefficient in the matrix of coefficients, and wherein each quantization value corresponds to a frequency in the range of frequencies having low frequencies and high frequencies, wherein the quantization values are defined to obtain a desired amount of data from processing the matrix of coefficients, wherein the quantization values in different quantization matrices are such that for increased compression, a quantization value corresponding to at least one higher frequency is changed whereas quantization values corresponding to at least one lower frequency is unchanged;

a quantizer for quantizing the coefficients for the block of the image data using the defined quantization matrix; and

an encoder for encoding the quantized coefficients to produce compressed image data.

14. The apparatus of claim 13, wherein for further compression, high frequency components above a cut-off frequency are filtered out by the quantization matrix.

15. The apparatus of claim 14, further comprising:

means for comparing an amount of data obtained from the encoding to a target amount of data; and

means for adjusting the cutoff frequency to increase compression if the amount of data is greater than the target amount.

16. The apparatus of claim 15, wherein the quantization matrix is defined such that quantization values below but near the cut-off frequency are changed to mute the corresponding frequency components.

17. The apparatus of claim 14, wherein the quantization matrix is defined such that quantization values below but near the cut-off frequency are changed to mute the corresponding frequency components.

18. The apparatus of claim 13, further comprising:

means for comparing an amount of data obtained from the encoding to a target amount of data; and

means for adjusting the quantization matrix to increase compression by changing a quantization value corresponding to at least one higher frequency whereas quantization values corresponding to lower frequencies are unchanged.

19. The apparatus of claim 13, wherein quantization values are larger for high frequencies than for low frequencies.

20. The apparatus of claim 13, wherein quantization values increase from low frequencies to high frequencies.

21. The apparatus of claim 13, wherein quantization values increase from low frequencies to a cutoff frequency, and wherein quantization values corresponding to frequencies above the cutoff frequency are a maximum value.

22. The apparatus of claim 13, further comprising means for storing the compressed image data in a data file.

23. The apparatus of claim 13, further comprising means for decompressing the compressed image data.

24. The apparatus of claim 23, wherein decompressing comprises:

means for decoding the compressed image data to produce a set of coefficients; and

means for performing an inverse transform on the set of coefficients to generate image data.