Signal to noise improvement

• US 9,185,412 B2
• Filed: 02/25/2014
• Issued: 11/10/2015
• 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:
  US14/189,424
• Publication Number:
  US 20140177972A1
• Time in Patent Office: 623 Days
• US Class Current: 1/1
• 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 processor executable code for high quality wide-range multi-layer image compression of a sequence of video images. A computer-implemented method of adding signal-to-noise improvement layers which are targeted to specific aspects of a sequence of images. The method comprises selecting one or more aspects of a coded image to improve, isolating those image aspects using the selection criteria, and coding a signal-to-noise layer using the isolated coded image aspects. A computer-implemented method for generating a signal-to-noise correction layer from a digitized video image represented as pixels. The method comprises quantizing and dequantizing the digitized video image to create a coded image, subtracting the coded image from the digitized video image to create a signal-to-noise difference image represented as pixels, and applying one or both of quantization weighting and pixel weighting to the signal-to-noise difference image pixel values such that larger difference image pixel values have smaller quantized values.

Claims

1. A computer-implemented method for compressing a sequence of digitized video images represented as pixels utilizing signal-to-noise improvement layers, the method being implemented in a computer system comprising one or more physical processors, the method comprising:

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

generating a plurality of signal-to-noise layers, each signal-to-noise layer being derived from a corresponding coded image layer, wherein at least one such signal-to-noise layer is targeted to improving the quality of a selected specific feature of the corresponding coded image layer.

2. The method of claim 1, wherein at least one generated processed image layer is a band-split layer.

3. The method of claim 1, further including encoding at least one generated processed image layer by preferentially allocating coding bits to regions of interest in such at least one generated processed image layer by decreasing the amplitude of pixel differences near edges of the corresponding digitized video image using a weighting which decreases as a function of nearness to such image edges.

4. The method of claim 1, wherein generating at least one processed image layer includes applying a filter structure to generate a hierarchy of reduced resolution layers from one of the sequence of digitized video images.

5. The method of claim 4, further including generating at least one signal-to-noise layer corresponding to at least one of the hierarchy of reduced resolution layers.

6. The method of claim 1, wherein the pixels of the sequence of digitized video images have values representing different colors within a color space, and further including:

generating at least one processed image layer by applying a non-linear function to each color value of the pixels of at least one of the sequence of digitized video images to create a perceptually weighted image; and

generating a signal-to-noise layer from each perceptually weighted image.

7. The method of claim 6, wherein the non-linear function is a gamma function.

8. The method of claim 6, wherein the non-linear function is a log function.

9. A computer-implemented method for compressing a sequence of digitized video images represented as pixels utilizing signal-to-noise improvement layers, the method being implemented in a computer system comprising one or more physical processors, the method comprising:

generating at least one processed image layer from at least one of the sequence of digitized video images, wherein each processed image layer comprises a plurality of values representing one of a coded image layer or a signal-to-noise layer derived from a coded image layer; and

encoding at least one generated processed image layer by preferentially allocating coding bits to regions of interest in such generated processed image layer by decreasing the amplitude of pixel differences near edges of the corresponding digitized video image using a weighting which decreases as a function of nearness to such image edges.

10. The method of claim 9, wherein generating at least one processed image layer includes applying a filter structure to generate a hierarchy of reduced resolution layers from one of the sequence of digitized video images.

11. The method of claim 10, further including generating at least one signal-to-noise layer, each such signal-to-noise layer corresponding to one of the hierarchy of reduced resolution layers.

12. The method of claim 9, wherein the pixels of the sequence of digitized video images have values representing different colors within a color space, and wherein generating at least one processed image layer includes:

applying a non-linear function to each color value of the pixels of at least one of the sequence of digitized video images to create a perceptually weighted image; and

generating a signal-to-noise layer from each perceptually weighted image.

13. The method of claim 12, wherein the non-linear function is a gamma function.

14. The method of claim 12, wherein the non-linear function is a log function.

15. The method of claim 9, wherein at least one generated processed image layer is a band-split layer.