System and method for noise reduction for blending blurred frames in a multi-frame system
A system and method are provided for noise reduction improvement for blending blurred frames in a multi-frame system. The method includes retrieving a number of frames of an image. The method also includes identifying one or more edges within the frames and comparing an edge strength of a reference frame and an edge strength of a non-reference frame. The method further includes determining a weight reduction factor based on a result of the comparison and applying the weight reduction factor to a blending of multiple frames of the number of frames of the image. In addition, the method includes displaying the blended frames.
1. An electronic device comprising:
a display; and
at least one processor configured to:
obtain a number of image frames;
determine a sharpest image frame from among the number of image frames, wherein the sharpest image frame is a most detailed image frame from among the number of image frames;
identify the sharpest image frame as a reference frame;
identify one or more edges within the image frames;
divide an edge strength of the reference frame by an edge strength of a non-reference frame to determine a reduction ratio;
determine a weight reduction factor based on the reduction ratio;
apply the weight reduction factor to a blending of multiple image frames of the number of image frames; and
initiate display of the blended image frames.
2. The electronic device of claim 1 , wherein the weight reduction factor indicates how much to reduce the blending at a particular area or pixel.
3. The electronic device of claim 1 , wherein the at least one processor is configured to reduce a blending rate of the weight reduction factor in response to a smaller reduction ratio.
4. The electronic device of claim 1 , wherein the at least one processor is configured to increase a blending rate of the weight reduction factor in response to a larger reduction ratio.
5. The electronic device of claim 1 , wherein the at least one processor is further configured to:
obtain and apply edge and image structure maps; and
combine the edge and image structure maps with the weight reduction factor to limit a blending reduction around areas where blur would degrade image quality.
6. The electronic device of claim 1 , wherein the at least one processor is configured to:
measure an edge strength at each point in the reference frame and the non-reference frame to respectively obtain the edge strength of the reference frame and the edge strength of the non-reference frame;
rank order each location of the edge strength;
measure a range of the edge strengths across all of the image frames at each location; and
set weight reduction curve parameters based on the range.
7. The electronic device of claim 1 , wherein the at least one processor is configured to obtain the number of image frames from a server.
8. A method comprising:
obtaining a number of image frames;
determining a sharpest image frame from among the number of image frames, wherein the sharpest image frame is a most detailed image frame from among the number of image frames;
identifying the sharpest image frame as a reference frame;
identifying one or more edges within the image frames;
dividing an edge strength of the reference frame by an edge strength of a non-reference frame to determine a reduction ratio;
determining a weight reduction factor based on the reduction ratio;
applying the weight reduction factor to a blending of multiple image frames of the number of image frames; and
displaying the blended image frames.
9. The method of claim 8 , wherein the weight reduction factor indicates how much to reduce the blending at a particular area or pixel.
10. The method of claim 8 , wherein a blending rate of the weight reduction factor is reduced in response to a smaller reduction ratio.
11. The method of claim 8 , wherein a blending rate of the weight reduction factor is increased in response to a larger reduction ratio.
12. The method of claim 8 , further comprising:
obtaining and apply edge and image structure maps; and
combining the edge and image structure maps with the weight reduction factor to limit a blending reduction around areas where blur would degrade image quality.
13. The method of claim 8 , further comprising:
measuring an edge strength at each point in the reference frame and the non-reference frame to respectively obtain the edge strength of the reference frame and the edge strength of the non-reference frame;
rank ordering each location of the edge strength;
measuring a range of the edge strengths across all of the image frames at each location; and
setting weight reduction curve parameters based on the range.
14. The method of claim 8 , wherein obtaining the number of image frames comprises obtaining the number of image frames from a server.
15. A non-transitory machine-readable medium containing instructions that, when executed by at least one processor of an electronic device, cause the at least one processor to:
obtain a number of image frames;
determine a sharpest image frame from among the number of image frames, wherein the sharpest image frame is a most detailed image frame from among the number of image frames;
identify the sharpest image frame as a reference frame;
identify one or more edges within the image frames;
divide an edge strength of the reference frame by an edge strength of a non-reference frame to determine a reduction ratio;
determine a weight reduction factor based on the reduction ratio;
apply the weight reduction factor to a blending of multiple image frames of the number of image frames; and
initiate display of the blended image frames.
16. The non-transitory machine-readable medium of claim 15 , wherein the weight reduction factor indicates how much to reduce the blending at a particular area or pixel.
17. The non-transitory machine-readable medium of claim 15 , wherein the instructions when executed cause the at least one processor to:
reduce a blending rate of the weight reduction factor in response to a smaller reduction ratio; and
increase the blending rate of the weight reduction factor in response to a larger reduction ratio.
18. The non-transitory machine-readable medium of claim 17 , further containing instructions that when executed cause the at least one processor to:
obtain and apply edge and image structure maps; and
combine the edge and image structure maps with the weight reduction factor to limit a blending reduction around areas where blur would degrade image quality.
19. The non-transitory machine-readable medium of claim 15 , further containing instructions that when executed cause the at least one processor to:
measure an edge strength at each point in the reference frame and the non-reference frame to respectively obtain the edge strength of the reference frame and the edge strength of the non-reference frame;
rank order each location of the edge strength;
measure a range of the edge strengths across all of the image frames at each location; and
set weight reduction curve parameters based on the range.
20. The non-transitory machine-readable medium of claim 15 , wherein the instructions when executed cause the at least one processor to obtain the number of image frames from a server.