IP Library Granted Patent US 8,687,905
Granted Patent B2
US 8,687,905 · App. 13/534,051 · Granted Apr 1, 2014

Method and device for selecting optimal transform matrices for down-sampling DCT image

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Quick Facts
Patent No.
US 8,687,905
App. No.
13/534,051
Granted
Apr 1, 2014
Kind
B2
Abstract

Down-sampling of an image may be performed in the DCT domain. Transform matrices are obtained for down-sampling a DCT image of size M×N to a down-sampled DCT image of size I×J. The transform matrices may be used to down-sample the DCT image directly in the DCT domain. A spatial domain down-sampling method is selected and applied to the DCT image to produce a down-sampled DCT reference image. The transform matrices are selected by solving an optimization problem, leading to transform matrices which achieve a desired trade-off between the visual quality of images obtained using the transform matrices and the computational complexity associated with using the transform matrices. The visual quality is a measure of the difference between the down-sampled DCT image obtained using the transform matrices and the visual quality of the DCT reference image obtained using a spatial domain down-sampling method.

Claims (92)

1. A method of selecting transform matrices for down-sampling in the discrete cosine transform (DCT) domain, the method comprising:

initializing the transform matrices;

obtaining at least one optimization parameter; and

selecting transform matrices to minimize an optimization expression, the optimization expression is a function of the at least one optimization parameter, wherein the at least one optimization parameter comprises a complexity trade-off parameter to balance the relative importance of a plurality of factors on the computational complexity of selecting transform matrices.

2. The method of claim 1 , wherein the at least one optimization parameter comprises a quality-and-complexity trade-off parameter to balance the relative importance of quality of an image down-sampled using the transform matrices and the computational complexity of selecting the transform matrices.

3. The method of claim 1 further comprising:

converting a DCT reference image into a spatial domain reference image;

applying a spatial domain down-sampling method to the spatial domain reference image to produce a spatial domain down-sampled reference image; and

converting the spatial domain down-sampled reference image to the DCT domain to produce a down-sampled DCT reference image, wherein the at least one optimization parameters comprises a quality-and-complexity trade-off parameter to adjust the trade-off between the error between a down-sampled image obtained using the transform matrices and the down-sampled DCT reference image.

4. The method of claim 3 , wherein selecting transform matrices includes determining the visual quality of the down-sampled DCT image obtained by applying the transform matrices to the DCT reference image relative to the visual quality of the down-sampled DCT reference image by calculating the mean squared error between the down-sampled DCT image obtained using the transform matrices and the down-sampled DCT reference image.

5. The method of claim 3 , wherein the transform matrices comprise a row-transform matrix and a column-transform matrix, and wherein selecting transform matrices includes determining the visual quality of down-sampled DCT images obtained by applying the row-transform matrix and the column-transform matrix to the DCT reference image, and determining the computational complexity associated with applying the row-transform matrix and the column-transform matrix to down-sample the DCT reference image.

6. The method of claim 3 , wherein the transform matrices comprise a row-transform matrix and a column-transform matrix, and wherein selecting transform matrices includes selecting transform matrices that satisfy the optimization expression:

min

D

IM

,

W

NJ

(

D

IM

·

C

MN

·

W

NJ

-

V

IJ

2

+

λ

·

r

g

)

,

where D IM is the row-transform matrix; W NJ is the column-transform matrix; C MN is the DCT image; D IM ·C MN ·W NJ is the down-sampled DCT image obtained using the transform matrices; V IJ is the down-sampled DCT reference image; r g is a measure of the computational complexity associated with using the transform matrices D IM , W NJ to down-sample an image C MN ; and λ is the quality-and-complexity trade-off parameter for balancing the trade-off between visual quality of the down-sampled DCT image and the computational complexity of obtaining the down-sampled DCT image.

7. The method of claim 1 , wherein the computational complexity is a function of the absolute values of elements in the transform matrices.

8. The method of claim 7 , further comprising calculating the summation of the absolute value of all elements in the transform matrices.

9. The method of claim 1 , wherein the at least one optimization parameter comprises a selective learning with forgetting threshold parameter and wherein the computational complexity is a function of the absolute values of all elements in the transform matrices below the selective learning with forgetting threshold parameter.

10. The method of claim 9 further comprising calculating the summation of the absolute values of all elements in the transform matrices below the selective learning with forgetting threshold parameter.

11. The method of claim 1 , wherein the computational complexity is a function of the number of non-zero elements in a binary representation of each element of the transform matrices.

12. An electronic device comprising:

a memory; and

a processor connected to the memory for obtaining transform matrices for down-sampling in the discrete cosine transform (DCT) domain, the processor being configured to:

initialize the transform matrices;

obtain at least one optimization parameter; and

select transform matrices to minimize an optimization expression, the optimization expression is a function of the at least one optimization parameter, wherein the at least one optimization parameter comprises a complexity trade-off parameter to balance the relative importance of a plurality of factors on the computational complexity.

13. The electronic device of claim 12 , wherein the at least one optimization parameter is retrieved from memory.

14. The electronic device of claim 12 , wherein the at least one optimization parameter comprises a quality-and-complexity trade-off parameter to balance the relative importance of quality of an image down-sampled using the transform matrices and the computational complexity of selecting the transform matrices.

15. The electronic device of claim 12 wherein the processor is further configured to:

convert a DCT reference image into a spatial domain reference image;

apply a spatial domain down-sampling method to the spatial domain reference image to produce a spatial domain down-sampled reference image; and

convert the spatial domain down-sampled reference image to the DCT domain to produce a down-sampled DCT reference image, wherein the at least one optimization parameter comprises a quality and complexity trade-off parameter to adjust the trade-off between the error between a down-sampled image obtained using the transform matrices and the down-sampled DCT reference image.

16. The electronic device of claim 15 , wherein selecting transform matrices includes determining the visual quality of the down-sampled DCT image obtained by applying the transform matrices to the DCT reference image relative to the visual quality of the down-sampled DCT reference image by calculating the mean squared error between the down-sampled DCT image obtained using the transform matrices and the down-sampled DCT reference image.

17. The electronic device of claim 15 wherein the transform matrices comprise a row-transform matrix and a column-transform matrix and wherein the optimization expression is:

min

D

IM

,

W

NJ

(

D

IM

·

C

MN

·

W

NJ

-

V

IJ

2

+

λ

·

r

g

)

,

where D IM is the row-transform matrix; W NJ is the column-transform matrix; C MN is the DCT image; D IM ·C MN ·W NJ is the down-sampled DCT image obtained using the transform matrices; V IJ is the down-sampled DCT reference image; r g is a measure of the computational complexity associated with using the transform matrices D IM , W NJ to down-sample an image C MN ; and λ is the quality-and-complexity trade-off parameter for balancing the trade-off between visual quality of the down-sampled DCT image and the computational complexity of obtaining the down-sampled DCT image.

18. The electronic device of claim 12 , wherein the at least one optimization parameter comprises a predetermined threshold parameter and wherein the processor is configured to ignore the computational complexity due to values in the transform matrices that are above the predetermined threshold parameter.

Assignments (5)
NUNC PRO TUNC ASSIGNMENT Recorded Jun 19, 2023
From: BLACKBERRY LIMITED
To: MALIKIE INNOVATIONS LIMITED
Reel/Frame 064270/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 16, 2023
From: BLACKBERRY LIMITED
To: MALIKIE INNOVATIONS LIMITED
Reel/Frame 064104/0103 →
CHANGE OF NAME Recorded Feb 7, 2014
From: RESEARCH IN MOTION LIMITED
To: BLACKBERRY LIMITED
Reel/Frame 032188/0837 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 27, 2012
From: SLIPSTREAM DATA INC.
To: RESEARCH IN MOTION LIMITED
Reel/Frame 028449/0297 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 27, 2012
From: YU, XIANG; YANG, EN-HUI; WANG, HAIQUAN
To: SLIPSTREAM DATA INC.
Reel/Frame 028449/0334 →