High quality wide-range multi-layer image compression coding system

• US 7,916,952 B2
• Filed: 09/12/2005
• Issued: 03/29/2011
• Est. Priority Date: 09/14/2004
• Status: Active Grant

• Current Assignee: Gary Demos
• Original Assignee: Gary Demos
• Inventors: Demos, Gary
• Primary Examiner(s): Alavi; Amir
• Application Number:
  US11/225,665
• Publication Number:
  US 20060071825A1
• Time in Patent Office: 2,024 Days
• Field of Search: 382/162, 382/168, 382/232, 382/233, 382/239, 382/240, 382/250, 382/251, 382260-264, 382/276, 382/277, 382/298, 382/299, 375/240.02, 375/240.03, 375/240.11, 375/240.19, 375/E7.026, 375/E7.088, 348/231.1, 348/231.2, 348/231.99, 348/398.1, 348/437.1, 348/438.1, 341/50, 341/67, 341/131
• US Class Current: 382/232
• CPC Class Codes: H03M 7/24 Conversion to or from floating-point codes
• CPC Class Codes: H04N 19/10 using adaptive coding
• 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 19/146 Data rate or code amount at the encoder output
• CPC Class Codes: H04N 19/162 User input
• CPC Class Codes: H04N 19/17 the unit being an image region, e.g. an object
• CPC Class Codes: H04N 19/187 the unit being a scalable video layer
• CPC Class Codes: H04N 19/29 involving scalability at the object level, e.g. video object layer [VOL]
• CPC Class Codes: H04N 19/61 in combination with predictive coding
• CPC Class Codes: H04N 19/63 using sub-band based transform, e.g. wavelets
• CPC Class Codes: H04N 19/635 characterised by filter definition or implementation details
• CPC Class Codes: H04N 19/85 using pre-processing or post-processing specially adapted for video compression

Abstract

Systems, methods, and computer programs for high quality wide-range multi-layer image compression coding, including consistent ubiquitous use of floating point values in essentially all computations; an adjustable floating-point deadband; use of an optimal band-split filter; use of entire SNR layers at lower resolution levels; targeting of specific SNR layers to specific quality improvements; concentration of coding bits in regions of interest in targeted band-split and SNR layers; use of statically-assigned targets for high-pass and/or for SNR layers; improved SNR by using a lower quantization value for regions of an image showing a higher compression coding error; application of non-linear functions of color when computing difference values when creating an SNR layer; use of finer overall quantization at lower resolution levels with regional quantization scaling; removal of source image noise before motion-compensated compression or film steadying; use of one or more full-range low bands; use of alternate quantization control images for SNR bands and other high resolution enhancing bands; application of lossless variable-length coding using adaptive regions; use of a folder and file structure for layers of bits; and a method of inserting new intra frames by counting the number of bits needed for a motion compensated frame.

Claims

1. A method for compressing a sequence of digitized video images, the method including:

applying a band-split filter structure to generate a band-split hierarchy from a digitized video image, the band-split hierarchy comprising at least two reduced resolution levels in which low-pass bands are created in between pixels of the digitized video image;

applying a different quantization parameter value to each of such at least two reduced resolution layers; and

performing subsequent encoding steps on such at least two reduced resolution layers to create a compressed output of such digitized video image.

2. The method of claim 1, further including the step of constraining at least one quantization parameter to a selected extreme value.

3. The method of claim 1, wherein at least one quantization parameter value has a floating-point numeric representation.

4. A method for compressing a sequence of digitized video images represented as pixels, the method including:

generating at least one processed layer from at least one of the digitized video images, each processed layer comprising a plurality of values; and

applying a quantization parameter to the plurality of values of such at least one processed layer using a lower quantization value for regions of such layer showing a higher compression coding error relative to a corresponding digitized video image or layer from which such processed layer was generated.

5. A method for compressing a sequence of digitized video images represented as pixels, the method including:

generating at least one processed layer from at least one of the digitized video images, each processed layer comprising a plurality of values; and

applying a quantization parameter to the plurality of values of such at least one processed layer using an adjustable size floating-point deadband for values of such processed layer near zero.

6. The method of claim 5, further including the step of adjusting the size of the deadband as a function of at least one of:

applying the quantiiation parameter to independent regions within one of such processed layers, or applying the quantization parameter to different processed layers.

7. The method of claim 5, wherein at least one processed layer is generated by the bi-orthogonal subband 9/7 discrete wavelet transform.

8. A method for compressing a sequence of digitized video images represented as pixels, the method including:

generating at least one processed layer from at least one of the digitized video images, each processed layer comprising a plurality of values;

dithering the values of at least one of such processed layers with pseudo-random noise prior to quantization; and

applying a quantization parameter to the plurality of values of such at least one processed layer.

9. The method of claim 8, wherein each value of each processed layer has an inherent noise level, and the quantization parameter has a step size, further including the step of setting the level of the pseudo-random noise such that the sum of the inherent noise and pseudo-random noise for at least each value outside of a deadband around zero approximates the quantization parameter step size.

10. A method for compressing a sequence of digitized video images represented as pixels, the method including:

generating a plurality of processed layers from at least one of the digitized video images;

applying a corresponding quantization parameter to each processed layer, each corresponding quantization parameter being scaled such that lower resolution layers have lower quantization parameter values relative to higher resolution layers; and

varying the value of the quantization parameter for each processed layer as a function of the region within such processed layer.

11. A method for reproducing the appearance of film grain or camera noise in compressed digitized video images, the method including:

applying a transform amplitude histogram as a function of one or more of color, brightness, and region for at least one signal-to-noise layer generated from such compressed digitized video images.