System and method for image enhancement

• US 20060104537A1
• Filed: 11/10/2005
• Published: 05/18/2006
• Est. Priority Date: 11/12/2004
• Status: Abandoned Application

• Current Assignee: Sozotek, Inc.
• Original Assignee: Sozotek, Inc.
• Inventors: Edgar, Albert D.
• Application Number:
  US11/271,707
• Publication Number:
  US 20060104537A1
• Time in Patent Office: Days
• US Class Current: 382/275
• CPC Class Codes: H04N 1/58 Edge or detail enhancement; Noise or error suppression, e.g. colour misregistration correction H04N1/62 takes precedence
• CPC Class Codes: H04N 1/6005 with luminance or chrominance signals, e.g. LC1C2, HSL or YUV

Abstract

Provided is a system and method for processing images. A method is provided for separating the image into two or more spatial phase data components, determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance, using the luminance value multiplier to determine one or more residue components for one or more of the two or more spatial phase data components, the residue components representing one or more concentrated noise components of the image, and performing noise reduction of the one or more residue components.

Claims

1. A method for enhancing an image, the method comprising:

separating the image into two or more spatial phase data components;

determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance;

using the luminance value multiplier to determine one or more residue components for one or more of the two or more spatial phase data components, the residue components representing one or more concentrated noise components of the image; and

performing noise reduction of the one or more residue components.

2. The method of claim 1 wherein the image is a region of a composite image including two or more regions, the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance being performed on the two or more regions of the composite image.

3. The method of claim 2 wherein the two or more regions of a composite image are 8×

8 pixel blocks of the image.

4. The method of claim 1 wherein the two or more spatial phase data components are an I channel including red spatial phase data minus blue spatial phase data, a Q channel including green spatial phase data minus magenta spatial phase data and/or magenta spatial phase data minus green spatial phase data, and a Y channel including a normalized sum of each of the Q and I channel color spatial phase data.

5. The method of claim 4 wherein the using the luminance value multiplier to determine one or more residue components for one or more of the two or more spatial phase data components, the residue components representing one or more concentrated noise components of the image includes:

measuring a magnitude of the Y channel, the I channel and the Q channel;

substantially removing the Y channel from the Q channel to produce a Q channel residue component as one of the residue components; and

substantially removing the Y channel from the I channel to produce an I channel residue component as one of the residue components.

6. The method of claim 4 wherein the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

calculating an I channel residue component by subtracting from the Y channel, the I channel multiplied by the I channel luminance value multiplier multiplied with the Y channel; and

calculating a Q channel residue component by subtracting from the Y channel the Q channel luminance value multiplier multiplied with the Y channel.

7. The method of claim 4 wherein the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

using the residue components as a predictor of noise present in the Y channel.

8. The method of claim 4 wherein the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance method includes:

performing a cross correlation of the Y channel with each of the Q channel and the I channel; and

dividing each cross correlation by an autocorrelation of the Y channel to obtain the luminance value multiplier.

9. The method of claim 4 wherein the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

determining Q channel luminance value multiplier by subtracting a power of the Y channel from a power of the Q channel and dividing a result by the power of the Y channel; and

determining an I channel luminance value multiplier by subtracting the power of the Y channel from the power of the I channel and dividing the result by the power of the Y channel.

10. The method of claim 1 wherein the performing noise reduction of the one or more residue components includes:

determining a phantom channel by performing a difference calculation between red-row green spatial phase data and blue-row green spatial phase data; and

performing the noise reduction using the phantom channel and the two or more residue components as estimates of noise in the image.

11. The method of claim 1 further comprising:

performing a high pass filtering to remove a base band bias from the image prior to determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance.

12. The method of claim 1 further comprising:

altering the Y channel using the one or more residue components following the noise reduction.

13. The method of claim 12 further comprising:

combining the altered Y channel, one or more residue components following the noise reduction and one or more cross correlation components to provide a deBayerized RGB image.

14. The method of claim 12 further comprising:

altering the Y channel using the one or more residue components following the noise reduction.

15. A computer program product comprising:

a signal bearing medium bearing;

one or more instructions for separating the image into two or more spatial phase data components;

one or more instructions for determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance;

one or more instructions for using the luminance value multiplier to determine one or more residue components for one or more of the two or more spatial phase data components, the residue components representing one or more concentrated noise components of the image; and

one or more instructions for performing noise reduction of the one or more residue components.

16. The computer program product of claim 15 wherein the signal bearing medium comprises:

a recordable medium.

17. The computer program product of claim 15 wherein the signal bearing medium comprises:

a transmission medium.

18. The computer program product of claim 15 wherein the image is a region of a composite image including two or more regions, the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance being performed on the two or more regions of the composite image.

19. The computer program product of claim 18 wherein the two or more regions of a composite image are 8×

8 pixel blocks of the image.

20. The computer program product of claim 15 wherein the two or more spatial phase data components are an I channel including red spatial phase data minus blue spatial phase data, a Q channel including green spatial phase data minus magenta spatial phase data and/or magenta spatial phase data minus green spatial phase data, and a Y channel including a normalized sum of each of the Q and I channel color spatial phase data.

21. The computer program product of claim 20 wherein the one or more instructions for using the luminance value multiplier to determine one or more residue components for one or more of the two or more spatial phase data components, the residue components representing one or more concentrated noise components of the image includes:

one or more instructions for measuring a magnitude of the Y channel, the I channel and the Q channel;

one or more instructions for substantially removing the Y channel from the Q channel to produce a Q channel residue component as one of the residue components; and

one or more instructions for substantially removing the Y channel from the I channel to produce an I channel residue component as one of the residue components.

22. The computer program product of claim 20 wherein the one or more instructions for determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

one or more instructions for calculating an I channel residue component by subtracting from the Y channel, the I channel multiplied by the I channel luminance value multiplier multiplied with the Y channel; and

one or more instructions for calculating a Q channel residue component by subtracting from the Y channel the Q channel luminance value multiplier multiplied with the Y channel.

23. The computer program product of claim 20 wherein the one or more instructions for the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

one or more instructions for using the residue components as a predictor of noise present in the Y channel.

24. The computer program product of claim 20 wherein the one or more instructions for the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

one or more instructions for performing a cross correlation of the Y channel with each of the Q channel and the I channel; and

one or more instructions for dividing each cross correlation by an autocorrelation of the Y channel to obtain the luminance value multiplier.

25. The computer program product of claim 20 wherein the one or more instructions for the determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance includes:

one or more instructions for determining Q channel luminance value multiplier by subtracting a power of the Y channel from a power of the Q channel and dividing a result by the power of the Y channel; and

one or more instructions for determining an I channel luminance value multiplier by subtracting the power of the Y channel from the power of the I channel and dividing the result by the power of the Y channel.

26. The computer program product of claim 15 wherein the performing noise reduction of the one or more residue components includes:

one or more instructions for determining a phantom channel by performing a difference calculation between red-row green spatial phase data and blue-row green spatial phase data; and

one or more instructions for performing the noise reduction using the phantom channel and the two or more residue components as estimates of noise in the image.

27. The computer program product of claim 15 further comprising:

one or more instructions for performing a high pass filtering to remove a base band bias from the image prior to determining a luminance value multiplier to enable the two or more spatial phase data components to match in luminance.

28. The computer program product of claim 15 further comprising:

one or more instructions for altering the Y channel using the one or more residue components following the noise reduction.

29. The computer program product of claim 28 further comprising:

one or more instructions for combining the altered Y channel, one or more residue components following the noise reduction and one or more cross correlation components to provide a deBayerized RGB image.

30. The computer program product of claim 28 further comprising:

one or more instructions for altering the Y channel using the one or more residue components following the noise reduction.

31. A computer system comprising:

a processor;

a memory coupled to the processor;

an image processing module coupled to the memory, the image processing module configured to attenuate noise and/or aliasing from an image sampled in a plurality of spatial phases, the image processing module including;

a measurement component to perform a difference calculation using at least two spatial phases; and

a selection component to select at least two of the plurality of spatial phases;

a luminance value multiplier component to enable the two or more spatial phase data components to match in luminance;

a residue component for using the one or more spatial phase data components to create one or more residue components representing concentrated noise components of the image.

32. The computer system of claim 31 wherein the image processing module is disposed in a mobile device.

33. The computer system of claim 31 wherein the image processing module is configured to receive image data via one or more of a wireless local area network (WLAN), a cellular and/or mobile system, a global positioning system (GPS), a radio frequency system, an infrared system, an IEEE 802.11 system, and a wireless Bluetooth system.

34. The computer system of claim 31 wherein the image processing module is configured to receive image data via one or more of a wireless local area network (WLAN), a cellular and/or mobile system, a global positioning system (GPS), a radio frequency system, an infrared system, an IEEE 802.11 system, and a wireless Bluetooth system.