Distortion-adaptive visual frequency weighting
First Claim
1. A method of compressing an image comprising the steps of:
- (a) separating data representing said image into a plurality of image data frequency sub-bands;
(b) transforming said data to a plurality of transform coefficients;
(c) mapping said transform coefficients to a plurality of quantizer indices, each said quantizer index comprising a plurality of digits arrayed from a most significant digit to a least significant digit;
(d) adding said most significant digits of said quantizer indices representing an image data frequency sub-band to a bitstream;
(e) repeating step (d) for a less significant digit of said quantizer indices until a number of significant digits specified by a truncation limit for said image data frequency sub-band is reached; and
(f) varying said truncation limit for at least two of said image data frequency sub-bands as a function of a distortion of said image, wherein the magnitude of the quantization is increased for higher frequencies relative to lower frequencies as the data rate of transmission of said image data decreases, wherein the magnitude of the quantization is decreased for higher frequencies relative to lower frequencies as the data rate of transmission of said image data increases.
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Abstract
The ability of the visual system to detect contrast in an image is a function of the frequency of the contrasting pattern and the distortion of the image. The visual system is more sensitive to contrasting patterns of lower frequency. When the image is significantly distorted, the visual system is even more sensitive to lower frequencies than higher frequencies. An image encoder employs lossy data compression processes producing a distorted reconstructed image. A method of quantizing image data including the step of varying the magnitude of a quantization step as a function of the distortion of an image is disclosed for further visually optimizing image quantization. Another method utilizes distortion adaptive weighting to vary the limit of code block truncation during embedded bitstream coding to visually optimize image compression by increasing relative lossiness of compression at higher frequencies.
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Citations
4 Claims
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1. A method of compressing an image comprising the steps of:
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(a) separating data representing said image into a plurality of image data frequency sub-bands; (b) transforming said data to a plurality of transform coefficients; (c) mapping said transform coefficients to a plurality of quantizer indices, each said quantizer index comprising a plurality of digits arrayed from a most significant digit to a least significant digit; (d) adding said most significant digits of said quantizer indices representing an image data frequency sub-band to a bitstream; (e) repeating step (d) for a less significant digit of said quantizer indices until a number of significant digits specified by a truncation limit for said image data frequency sub-band is reached; and (f) varying said truncation limit for at least two of said image data frequency sub-bands as a function of a distortion of said image, wherein the magnitude of the quantization is increased for higher frequencies relative to lower frequencies as the data rate of transmission of said image data decreases, wherein the magnitude of the quantization is decreased for higher frequencies relative to lower frequencies as the data rate of transmission of said image data increases. - View Dependent Claims (2, 3, 4)
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Specification