Multiple color channel multiple regression predictor

Patent metadata

Field	Value
Publication number	US-10021390-B2
Application number	US-201715608433-A
Country	US
Kind code	B2
Filing date	May 30, 2017
Priority date	Apr 14, 2011
Publication date	Jul 10, 2018
Grant date	Jul 10, 2018

Abstract

Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

First claim

What is claimed is:

1. In an encoding or decoding video system, an image prediction method with a processor, the method comprising:
receiving a first image;
receiving prediction parameters for a multi-channel multiple-regression (MMR) prediction model, wherein the MMR model is adapted to predict a second image in terms of the first image; and
applying the first image and the prediction parameters to the MMR prediction model to generate an output image approximating the second image, wherein pixel values of at least one color component of the output image are computed based on pixel values of at least two color components in the first image, wherein for generating a predicted output pixel value ({circumflex over (v)} i ) for a luma and/or chroma component the MMR model comprises a first order MMR model with cross products comprising: a constant value (n), at least a linear combination of pixel values of two different color components, and at least one product term of pixel values of two different color components.

2. The method of claim 1 , wherein the MMR model computes the predicted output pixel value ({circumflex over (v)} i ) according to the formula:
{circumflex over (v)} i =n+Σ k=1 3 m k (1) s ik +mc 1 (1) s i1 s i2 +mc 2 (1) s i1 s i3 +mc 3 (1) s i2 s i3 +mc 4 (1) s i1 s i2 s i3 ,

where s ik , k=1, 2, and 3, denote the three color components of the i-th pixel of the first image, and m k (1) (for k=1, 2, and 3), n, and mc j (1) (j=1, 2, 3, 4) denote the prediction parameters of the MMR model.

3. The method of claim 1 , wherein the first image and the second image have different dynamic ranges.

4. The method of claim 1 , wherein the dynamic range of the first image is lower than the dynamic range of the second image.

5. The method of claim 3 , wherein the first image is a standard dynamic range image and the second image is a high dynamic range image.

6. The method of claim 1 , wherein the MMR model further comprises at least a square of the pixel value of one of the color components and at least a square of a product of pixel values of two different color components to form a second MMR model with cross products.

7. The method of claim 6 , wherein the MMR model computes the predicted output pixel value ({circumflex over (v)} i ) according to the formula:
{circumflex over (v)} i =n+Σ k=1 3 m k (1) s ik +mc 1 (1) s i1 s i2 +mc 2 (1) s i1 s i3 +mc 3 (1) s i2 s i3 +mc 4 (1) s i1 s i2 s i3 +Σ k=1 3 m k (2) s ik 2 +mc 1 (2) ( s i1 s i2 ) 2 +mc 2 (2) ( s i1 s i3 ) 2 +mc 3 (2) ( s i2 s i3 ) 2 +mc 4 (2) ( s i1 s i2 s i3 ) 2 ,

where m k (2) and mc j (2) for k=1, 2, 3, and j=1, 2, 3, 4 denote additional parameters of the MMR model.

8. A video system, the system comprising:
an input for receiving a first image and prediction parameters for a multi-channel multiple-regression (MMR) prediction model, wherein the MMR model is adapted to predict a second image in terms of the first image;
a processor for applying the first image and the prediction parameters to the MMR prediction model to generate an output image approximating the second image, wherein pixel values of at least one color component of the output image are computed based on pixel values of at least two color components in the first image, wherein for generating a predicted output pixel value ({circumflex over (v)} i ) for a luma and/or chroma component the MMR model comprises a first order MMR model with cross products comprising: a constant value (n), at least a linear combination of pixel values of two different color components, and at least one product term of pixel values of two different color components.

9. The system of claim 8 , wherein the MMR model computes the predicted output pixel value ({circumflex over (v)} i ) according to the formula:
{circumflex over (v)} i =n+Σ k=1 3 m k (1) s ik +mc 1 (1) s i1 s i2 +m 2 (1) s i1 s i3 +mc 3 (1) s i2 s i3 +mc 4 (1) s i1 s i2 s i3 ,

where s ik , k=1, 2, and 3, denote the three color components of the i-th pixel of the first image, and m k (1) (for k=1, 2, and 3), n, and mc j (1) (for j=1, 2, 3, 4) denote the prediction parameters of the MMR model.

10. The system of claim 8 , wherein the dynamic range of the first image is lower than the dynamic range of the second image.

11. The system of claim 8 , wherein the first image is a standard dynamic range image and the second image is a high dynamic range image.

12. The system of claim 8 , wherein the MMR model further comprises at least a square of the pixel value of one of the color components and at least a square of a product of pixel values of two different color components.

13. The system of claim 12 , wherein the MMR model computes the predicted output pixel value ({circumflex over (v)} i ) according to the formula:
{circumflex over (v)} i =n+Σ k=1 3 m k (1) s ik +m 1 (1) s i1 s i2 +mc 2 (1) s i1 s i3 +mc 3 (1) s i2 s i3 +mc 4 (1) s i2 s i3 +Σ k=1 3 m k (2) s ik 2 +mc 1 (2) ( s i1 s i2 ) 2 +m 2 (2) ( s i1 s i3 ) 2 +mc 3 (2) ( s i2 s i3 ) 2 +mc 4 (2) ( s i1 s i2 s i3 ) 2 ,

where m k (2) and mc j (2) for k=1, 2, 3, and j=1, 2, 3, 4 denote additional parameters of the MMR model.

14. A non-transitory computer-readable storage medium having stored thereon computer-executable instructions for executing with one or more processors a method in accordance with claim 1 .

Assignees

• Dolby Laboratories Licensing Corp

Inventors

• Su Guan-Ming
• Qu Sheng
• Koepfer Hubert
• Yuan Yufei
• Hulyalkar Samir

Classifications

• H04N19/98

  Adaptive-dynamic-range coding [ADRC] · CPC title

• H04N19/16

  for a given display mode, e.g. for interlaced or progressive display mode · CPC title

• H04N19/192

  the adaptation method, adaptation tool or adaptation type being iterative or recursive · CPC title

• H04N19/105 Primary

  Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction · CPC title

• H04N19/30

  using hierarchical techniques, e.g. scalability (H04N19/63 takes precedence) · CPC title