Compression of signals, images and video for multimedia, communications and other applications

• US 9,998,763 B2
• Filed: 03/31/2016
• Issued: 06/12/2018
• Est. Priority Date: 03/31/2015
• Status: Active Grant

• Current Assignee: Nxgen Partners Ip, LLC (NxGen Partners LLC)
• Original Assignee: Nxgen Partners Ip, LLC (NxGen Partners LLC)
• Inventors: Ashrafi, Solyman, Linquist, Roger D.
• Primary Examiner(s): Messmore, Jonathan
• Application Number:
  US15/087,540
• Publication Number:
  US 20160295243A1
• Time in Patent Office: 803 Days
• Field of Search: 37524019
• CPC Class Codes: H04N 19/18 the unit being a set of transform coefficients
• CPC Class Codes: H04N 19/182 the unit being a pixel
• CPC Class Codes: H04N 19/186 the unit being a colour or a chrominance component
• CPC Class Codes: H04N 19/63 using sub-band based transform, e.g. wavelets
• CPC Class Codes: H04N 19/91 Entropy coding, e.g. variable length coding [VLC] or arithmetic coding

Abstract

A system and method for transmitting compressed image data includes an encoder, responsive to received image data representing an image, for minimizing a space-spatial frequency of the image data by applying a predetermined orthogonal function thereto to generate a mathematical representation of the image data and extracting coefficients of the mathematical representation of the image data. A transmitter transmits the coefficients of the image data from a first location to a second location. A receiver receives the transmitted coefficients of the image data at the second location from the first location. A decoder recreates the mathematical representation of the image data at the second location responsive to the received coefficients and the predetermined orthogonal function and generates the image data from the recreated mathematical representation of the image data.

Claims

1. A method for transmitting compressed image data comprising:

receiving image data representing an image;

minimizing a space-spatial frequency product of the image data by applying a predetermined Hermite-Gaussian function thereto to generate a minimized mathematical representation of the image data, wherein the minimized space-spatial frequency product of the image data equals ½

;

extracting coefficients contained within the generated minimized mathematical representation of the image data;

transmitting the extracted coefficients of the minimized mathematical representation of the image data without any remaining portions of the minimized mathematical representation of the image data from a first location to a second location;

recreating the minimized mathematical representation of the image data comprising the minimized space-spatial frequency product of the image data at the second location responsive to the transmitted extracted coefficients and the predetermined Hermite-Gaussian function stored at the second location; and

generating the image from the recreated minimized mathematical representation of the image data comprising the space-spatial frequency product of the image data.

2. The method of claim 1, wherein the image data comprises video data.

3. The method of claim 1, wherein the step of minimizing further comprises generating the minimized mathematical representation of the image data responsive to the Hermite-Gaussian function and at least one of complex moments and geometric moments.

4. The method of claim 1, wherein the step of minimizing further comprises minimizing the space-spatial frequency of the image data by applying a waveletized version of the Hermite-Gaussian function to generate the minimized mathematical representation of the image data.

5. The method of claim 1, wherein the step of minimizing further comprises:

determining each pixel represented in the received image data;

determining a central moment of the image from the received image data;

determining a moment reference of each pixel to the central moment of the image; and

generating the mathematical representation of the image data from the determined moments of reference for each of the pixels.

6. The method of claim 1, wherein the step of minimizing further comprises compressing color data represented by the image data.

7. The method of claim 6, wherein the predetermined Hermite-Gaussian function further comprises a quaternionic Hermite-Gaussian Function.

8. The method of claim 7, wherein the minimization by applying the quaternionic Hermite-Gaussian function further applies a quaternion Fourier transform to the image data.

9. The method of claim 7, wherein the step of compressing color data further comprises:

assigning red color data of RGB data to a first component of the quaternionic Hermite-Gaussian Function;

assigning green color data of the RGB data to a second component of the quaternionic Hermite-Gaussian Function; and

assigning blue color data of the RGB data to a third component of the quaternionic Hermite-Gaussian Function.

10. The method of claim 6, wherein the step of compressing further comprises:

converting RGB color data into luma data and chroma data;

assigning the luma data to a first component of the predetermined Hermite-Gaussian function; and

assigning the chroma data to at least one of a second component and component of the predetermined Hermite-Gaussian function.

11. The method of claim 1, wherein the step of minimizing further comprises decomposing the image data using a quaternionic singular value decomposition.

12. A system for transmitting compressed image data, comprising:

an encoder, responsive to received image data representing an image, for minimizing a space-spatial frequency product of the image data by applying a predetermined Hermite-Gaussian function thereto to generate a minimized mathematical representation of the image data, wherein the minimized space-spatial frequency product of the image data equals ½

, the encoder further extracting coefficients of the minimized mathematical representation of the image data;

a transmitter for transmitting the coefficients of the minimized mathematical representation of the image data without any remaining portions of the minimized mathematical representation of the image data from a first location to a second location;

a receiver for receiving the transmitted extracted coefficients of the minimized mathematical representation of the image data at the second location from the first location; and

a decoder for recreating the minimized mathematical representation of the image data comprising the minimized space-spatial frequency product of the image data at the second location responsive to the received extracted coefficients and the predetermined Hermite-Gaussian function that is stored at the decoder and generating the image data from the recreated mininmized mathematical representation of the image data comprising the space-spatial frequency product of the image data.

13. The system of claim 12, wherein the image data comprises video data.

14. The system of claim 12, wherein the encoder further generates the minimized mathematical representation of the image data responsive to the Hermite-Gaussian function and at least one of complex moments and geometric moments.

15. The system of claim 12, wherein the encoder further minimizes the space-spatial frequency of the image data by applying a waveletized version of the Hermite-Gaussian function to generate the minimized mathematical representation of the image data.

16. The system of claim 12, wherein the encoder further determines each pixel represented in the received image data, determines a central moment of the image from the image data, determines a moment reference of each pixel to the central moment of the image and generates the minimized mathematical representation of the image data from the determined moments of reference for each of the pixels.

17. The system of claim 12, wherein the encoder further compresses color data represented by the image data.

18. The system of claim 17, wherein the predetermined Hermite-Gaissian function further comprises a quaternionic Hermite-Gaussian Function.

19. The system of claim 18, wherein the encoder applies a quaternion Fourier transform to the image data.

20. The system of claim 18, wherein the encoder further assigns red color data of RGB data to a first component of the quaternionic Hermite-Gaussian Function, assigns green color data of the RGB data to a second component of the quaternionic Hermite-Gaussian Function and assigns blue color data of the RGB data to a third component of the quaternionic Hermite-Gaussian Function.

21. The system of claim 17, wherein the encoder further converts RGB color data into luma and chroma data, assigns the luma data to a first component of the predetermined Hermite-Gaussian and assigns the chroma data to at least one of a second component and third component of the predetermined Hermite-Gaussian function.

22. The system of claim 12, wherein the encoder decomposes the image data using a quaternionic singular value decomposition.

23. A method for transmitting compressed video data comprising:

receiving video data representing a video, the video data representing color data for each pixel making up the video;

processing the video data by applying a predetermined hyper-complex quaternion Hermite-Gaussian function thereto to generate a minimized mathematical representation of the video data, wherein the step of processing further comprises;

assigning red color data of RGB data to a first component of the hyper-complex quaternion Hermite-Gaussian function;

assigning green color data of the RGB data to a second component of the hyper-complex quaternion Hermite-Gaussian function;

assigning blue color data of the RGB data to a third component of the hyper-complex quaternion Hermite-Gaussian function;

assigning a zero value to a forth component of the hyper-complex quaternion Hermite-Gaussian function;

extracting coefficient contained within the generated minimized mathematical representation of the video data;

transmitting the extracted coefficients of the minimized mathematical representation of the video data from without any remaining portion of the minimized mathematical representation of the image data from a first location to a second location;

recreating the minimized mathematical representation of the video data at the second location responsive to the transmitted extracted coefficients and the three components assigned to the red, green and blue color data of the predetermined hyper-complex quaternian Hermite-Gaussian function stored at the second location; and

generating the video from the recreated minimized mathematical representation of the video data.

24. A method for transmitting compressed image data comprising:

receiving image data representing an image;

processing each pixel of each frame of the image data to determine moments to minimize a space-spatial frequency product of the image data and generate a minimized mathematical representation of the image data responsive to a predetermined Hermite-Gaussian function, wherein the minimized space-spatial frequency product of the image data equals ½

;

extracting coefficients from the minimized mathematical representation of the image data;

transmitting the extracted coefficients of the minimized mathematical representation of the image data without any remaining portions of the mathematical representation of the image data from a first location to a second location;

recreating the minimized mathematical representation of the image data comprising the minimized space-spatial frequency product of the image data at the second location responsive to the transmitted extracted coefficients and the predetermined Hermite-Gaussian function stored at the second location; and

generating the image from the recreated minimized mathematical representation of the image data comprising the minimized space-spatial frequency product of the image data.

25. The method of claim 24, wherein the step of processing further comprises:

determining each pixel represented in the received video data;

determining a central moment of an image from the video data;

determining a moment reference of each pixel to the central moment of the image; and

generating the minimized mathematical representation of the video data from the determined moments of reference for each of the pixels.