METHOD AND APPARATUS FOR IMAGE PROCESSING

• US 20130222689A1
• Filed: 04/15/2013
• Published: 08/29/2013
• Est. Priority Date: 04/23/2007
• Status: Active Grant

• Current Assignee: Comagna KFT
• Original Assignee: Comagna KFT
• Inventors: LIGETI, Gabor
• Granted Patent: US 9,189,838 B2
• Time in Patent Office: Days
• US Class Current: 348/441
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/60 using machine learning, e.g. neural networks
• CPC Class Codes: H04N 7/0125 one of the standards being a high definition standard

Abstract

The present invention discloses a system and method of transforming a sample of content data by utilizing known samples in a learning phase to best determine coefficients for a linear combination of non-linear filter functions and applying the coefficients to the content data in an operational phase.

Claims

1. A method of transforming content data using a learning phase and a operational phase comprising:

a training phase comprising;

providing at least one sample of high-quality content and a

transform, wherein the transform is defined by a linear combination of pre-selected non-linear functions weighted with coefficients;

the at least one sample of high-quality content to produce a degraded quality content, resulting in a representative target sample;

applying the transform to the representative target sample; and

determining values for the coefficients that will best transform the representative target sample to resemble the at least one sample of high-quality content, resulting in optimized coefficients; and

an operational phase comprising;

providing at least one new sample; and

applying the transform and the optimized coefficients to the at least one new sample, resulting in enhanced content data.

2. The method of transforming content data according to claim 1, wherein the content data is image data captured with a camera using a Bayer filter.

3. The method of transforming content data according to claim 2, wherein the transform at least partially comprises a filter for demosaicing.

4. The method of transforming content data according to claim 1, wherein the content data is image data, and wherein the transform at least partially comprises a filter for performing a function selected from among:

resolution enhancement, filtering, noise reduction, color filter demosaicing, zooming, edge enhancement and sharpening.

5. The method of transforming content data according to claim 1, wherein the content data is medical imaging data.

6. The method of transforming content data according to claim 1, the method further comprising a pre-emphasis phase and a de-emphasis phase.

7. A system for transforming content data comprising:

at least one content data source;

an image processing apparatus comprising;

transform memory containing a set of at least one pre-selected filter function weighted with at least one coefficient;

a known data memory containing at least one known content sample;

a target sample memory;

a down-sampling processor, wherein the down-sampling processor obtains a known content sample from the known data memory and performs a down-sampling transform, resulting in a target sample;

a target sample memory;

a learning phase processor, wherein the learning phase processor obtains a known content sample, at least one pre-selected filter function, and a target sample, and wherein the learning phase processor

determines the best coefficients for transforming the target sample to the known content sample, resulting in at least one optimal coefficient; and

an operational phase processor, wherein the operational phase processor obtains at least one preselected filter function, at least one optimal coefficient and content data from the at least one content data source, and wherein the content data is transformed using the at least one filter function and the at least one optimal coefficient, resulting in transformed content data; and

an output.

8. The system for transforming content data according to claim 7, wherein the at least one pre-selected filter function comprises a linear combination of pre-selected non-linear functions.

9. The system for transforming content data according to claim 7, wherein at least one content data source is selected from among:

image-capture devices, scanners, video capture devices, medical imaging devices, streaming video sources, and generated video sources.

10. The system for transforming content data according to claim 7, wherein the image processing apparatus is incorporated into a television cable modem, wherein the at least one content source is a low resolution television signal, wherein the set of at least one pre-selected filter function comprises at least partially a resolution enhancement function, and

wherein the output is a high resolution television signal.

11. The system for transforming content data according to claim 10, wherein the low-resolution television signal comprises a low resolution interlaced television signal, wherein the set of at least one pre-selected filter function comprises at least partially a de-interlacing function, and wherein the output is a high resolution progressive scan television signal.