Systems and methods for dynamic refocusing of high resolution images generated using images captured by a plurality of imagers

• US 9,041,824 B2
• Filed: 10/21/2014
• Issued: 05/26/2015
• Est. Priority Date: 12/14/2010
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: Pelican Imaging Corporation
• Inventors: Lelescu, Dan, Molina, Gabriel, Venkataraman, Kartik
• Primary Examiner(s): Ye, Lin
• Assistant Examiner(s): YODER III, CHRISS S
• Application Number:
  US14/520,269
• Publication Number:
  US 20150036015A1
• Time in Patent Office: 217 Days
• Field of Search: 348/218.1, 348/335, 348/340, 250/208.1, 382/106, 382/276
• US Class Current: 348/218.1
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging
• CPC Class Codes: G06T 3/4007 based on interpolation, e.g. bilinear interpolation image demosaicing G06T3/4015; edge-driven or edge-based scaling G06T3/403
• CPC Class Codes: G06T 3/4053 based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
• CPC Class Codes: G06T 3/4076 using the original low-resolution images to iteratively correct the high-resolution images
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 5/80 Geometric correction
• CPC Class Codes: H04N 13/106 Processing image signals for multi-view video sequence encoding H04N19/597
• CPC Class Codes: H04N 13/111 Transformation of image signals corresponding to virtual viewpoints, e.g. spatial image interpolation
• CPC Class Codes: H04N 13/128 Adjusting depth or disparity
• CPC Class Codes: H04N 13/139 Format conversion, e.g. of frame-rate or size
• CPC Class Codes: H04N 13/156 Mixing image signals
• CPC Class Codes: H04N 13/204 using stereoscopic image cameras stereoscopic photography G03B35/00
• CPC Class Codes: H04N 13/246 Calibration of cameras
• CPC Class Codes: H04N 13/271 : wherein the generated image signals comprise depth maps or disparity maps
• CPC Class Codes: H04N 23/62 : Control of parameters via user interfaces
• CPC Class Codes: H04N 23/951 : by using two or more images to influence resolution, frame rate or aspect ratio

Abstract

Systems and methods in accordance with embodiments of the invention are disclosed that use super-resolution (SR) processes to use information from a plurality of low resolution (LR) images captured by an array camera to produce a synthesized higher resolution image. One embodiment includes obtaining input images, determining an initial estimate of at least a portion of a high resolution image using a plurality of pixels from the input images, and determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image. In addition, each forward imaging transformation corresponds to the manner in which each imager generates the input images, and the high resolution image has a resolution that is greater than any of the input images.

Claims

1. A method of generating a high resolution image of a scene using an imager array including a plurality of imagers that each capture an image of the scene, and a forward imaging transformation for each imager, the method comprising:

obtaining input images captured by a plurality of imagers using a processor configured by image processing pipeline software;

determining an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the input images using the processor configured by the image processing pipeline software;

determining a high resolution image that when mapped through a forward imaging transformation matches the input images to within at least one predetermined criterion using the processor configured using the image processing pipeline software based upon the initial estimate of at least a portion of the high resolution image, where;

each forward imaging transformation corresponds to the manner in which each imager in the plurality of imagers captures the input images; and

the high resolution image has a resolution that is greater than any of the input images; and

generating a depth map for the high resolution image using a processor configured by image processing pipeline software;

determining a focus map for the high resolution image using the depth map using a processor configured by image processing pipeline software; and

performing dynamic refocus of the high-resolution image using a processor configured by image processing pipeline software by rendering the high resolution image using the focus map.

2. The method of claim 1, wherein generating the depth map further comprises:

determining depth information for pixels in the high resolution image based upon the input images, parallax information, and the characteristics of the imager array; and

interpolating the depth information to obtain depth information for every pixel in the high resolution image.

3. The method of claim 1, wherein the focus map identifies pixels having depths in the depth map that are within a specified depth of a defined focal plane.

4. The method of claim 1, wherein the input images capture a scene in which depths of points in the imaged scene vary and each of the input images differs from the other input images due to:

scene independent geometric distortions inherent to the optics and manufacturing processes used to fabricate each of the plurality of imagers; and

scene dependent geometric displacements due to parallax based upon the depths of the points in the imaged scene.

5. The method of claim 4, further comprising:

determining scene dependent parallax information with respect to the input images based upon disparity relative to a reference point of view resulting from the depths of points in the imaged scene using the processor configured by the image processing pipeline software, where the scene dependent parallax information comprises scene dependent geometric transformations; and

determining a total shift for each of a plurality of pixels relative to the reference point of view, where the total shift of a given pixel location is the combination of a scene independent geometric correction determined for the given pixel location using geometric calibration data and the scene dependent geometric transformation determined for the given pixel location;

wherein determining an initial estimate of at least a portion of a high resolution image further comprises determining an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the input images based upon a total shift for each of the plurality of pixels relative to the reference point of view;

wherein each forward imaging transformation comprises applying geometric transformations based upon the total shift at a given pixel location, which is the combination of a scene independent geometric correction determined for the given pixel location using geometric calibration data and the scene dependent geometric transformation determined for the given pixel location.

6. The method of claim 5, wherein generating the depth map further comprises:

determining depth information for pixels in the high resolution image based upon the input images, scene dependent parallax information with respect to the input images based upon disparity relative to the reference viewpoint resulting from the depths of points in the imaged scene, and the characteristics of the imager array; and

interpolating the depth information to obtain depth information for every pixel in the high resolution image.

7. The method of claim 6, wherein the focus map identifies pixels having depths in the depth map that are within a specified depth of a defined focal plane.

8. The method of claim 5, wherein the forward imaging transformation further comprises applying scene independent geometric transformations related to the different geometries of each of the imagers in the plurality of imagers.

9. The method of claim 5, wherein the forward imaging transformation further comprises applying photometric transformations related to the different photometric characteristics of each of the imagers in the plurality of imagers.

10. The method of claim 5, wherein:

determining the initial estimate of at least a portion of the high resolution image comprises using an imaging prior including the geometric calibration data and applying scene independent geometric corrections to the input images using the geometric calibration data to obtain geometrically registered input images; and

determining the high resolution image that when mapped through the forward imaging transformation matches the input images to at least one predetermined criterion comprises determining the high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion.

11. The method of claim 5, wherein:

the depths of points in the imaged scene vary due to the presence of foreground and background objects;

each of the input images also differ from the other input images due to occlusion zones surrounding foreground objects; and

the scene dependent parallax information also includes occlusion maps.

12. The method of claim 5, wherein determining an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the captured images further comprises fusing at least portions of the input images to form the initial estimate of at least one portion of the high resolution image.

13. The method of claim 12, wherein fusing at least portions of the input images to form the initial estimate of at least one portion of the high resolution image comprises:

populating a high resolution grid corresponding to the pixel locations of the at least a portion of the initial estimate of the high resolution image with pixels from the input images using the total shift for the pixels; and

interpolating the high resolution grid to obtain filtered pixel values for each pixel in the initial estimate of the high resolution image.

14. The method of claim 5, wherein determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image comprises:

transforming the initial estimate of at least a portion of the high resolution image using at least one forward imaging transformation;

comparing the transformed initial estimate of at least a portion of the high resolution image to at least a portion of at least one input image; and

refining the estimate of the high resolution image based upon the comparison.

15. The method of claim 14, wherein determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image further comprises transforming, comparing and refining estimates until the at least one predetermined criterion is satisfied.

16. The method of claim 14, wherein transforming an estimate of at least a portion of the high resolution image using at least one forward imaging transformation, comprises:

applying geometric transformations including geometric transformations related to parallax observed in the imaged scene to the pixels of the estimate of at least a portion of the high resolution image;

applying a blur function to the pixels of the estimate of at least a portion of the high resolution image; and

decimating the warped and blurred pixels of the estimate of at least a portion of the high resolution image.

17. The method of claim 14, wherein refining the estimate of the high resolution image based upon the comparison comprises:

mapping the comparison of the transformed initial estimate of at least a portion of the high resolution image and the at least a portion of at least one input image through a backward imaging transformation, which is the reverse of the forward imaging transformation; and

updating the estimate using at least the transformed comparison.

18. The method of claim 5, wherein determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image, comprises:

identifying pixels in the initial estimate of at least a portion of the high resolution image corresponding to pixels in at least one input image using at least one forward imaging transformation;

comparing the corresponding pixels; and

refining the estimate of the high resolution image based upon the comparison.

19. The method of claim 18, wherein determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image, further comprises applying a blur function to pixels in the initial estimate of at least a portion of the high resolution image.

20. The method of claim 19, wherein identifying pixels in the initial estimate of at least a portion of the high resolution image corresponding to pixels in at least one input image using at least one forward imaging transformation comprises:

selecting a pixel position in the initial estimate of at least a portion of the high resolution image; and

using geometric transformations including geometric transformations related to parallax observed due to the depths of points in the imaged scene to identify pixels in at least a portion of at least one input image.

21. The method of claim 20, wherein the geometric transformations further comprise scene independent geometric transformations.

22. The method of claim 20, wherein using geometric transformations to identify pixels in at least a portion of at least one input image comprises:

identifying at least one pixel in the input image specified by the geometric transformation for at least the selected pixel from the initial estimate of at least a portion of the high resolution image, when a geometric transformation exists for the pixel in the initial estimate of at least a portion of the high resolution image; and

identifying at least one pixel in at least one input image based upon the geometric transformations of pixels in the neighborhood of the selected pixel from the initial estimate of at least a portion of the high resolution image, when a geometric transformation does not exist for the pixel in the initial estimate of at least a portion of the high resolution image.

23. The method of claim 18, wherein comparing corresponding pixels comprises determining differences between pixels in the initial estimate of at least a portion of the high resolution image and the identified corresponding pixels in at least one input image.

24. The method of claim 1, wherein determining a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image comprises:

generating an estimate of at least a portion of the high resolution image; and

applying an intra-channel prior filter to the estimate of at least a portion of the high resolution image, where the intra-channel prior filter is configured to preserve edges while removing noise.

25. The method of claim 1, wherein:

the imager array captures images in multiple color channels; and

the initial estimate of at least a portion of a high resolution image is an initial estimate of at least a portion of a high resolution image in a first color channel.

26. The method of claim 25, further comprising:

placing a plurality of pixels from input images in a second color channel on a high resolution grid; and

determining at least a portion of a high resolution image in the second color channel using at least the pixels in the second color channel placed on the high resolution grid and at least a portion of a high resolution image in another color channel.

27. The method of claim 26, wherein determining at least a portion of a high resolution image in the second color channel using at least the pixels in the second color channel placed on the high resolution grid and at least a portion of a high resolution image in another color channel comprises:

interpolating the pixels on the high resolution grid based upon their correlation with the pixels in the at least a portion of the high resolution image in the other color channel and the correlation between pixels in the high resolution image in the other color channel.

28. The method of claim 27, wherein the high resolution image that is determined using the initial estimate of at a least a portion of the high resolution image in a first color channel that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion is a high resolution image in the first color channel.

29. The method of claim 27, wherein the high resolution image that is determined using the initial estimate of at a least a portion of the high resolution image in a first color channel that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion is a high resolution image in multiple color channels.

30. A method of generating a high resolution image of a scene using an imager array including a plurality of imagers that each capture an image of the scene, and a forward imaging transformation for each imager, the method comprising:

obtaining input images captured by a plurality of imagers using a processor configured by image processing pipeline software, where the input images capture a scene in which depths of points in the imaged scene vary and each of the input images differs from the other input images due to;

scene independent geometric distortions inherent to the optics and manufacturing processes used to fabricate each of the plurality of imagers; and

scene dependent geometric displacements due to parallax experienced by each of the plurality of imagers based upon the different depths of the points in the imaged scene; and

determining scene dependent parallax information with respect to the input images based upon disparity relative to a reference point of view resulting from the different depths of points in the imaged scene using the processor configured by the image processing pipeline software, where the scene dependent parallax information comprises scene dependent geometric transformations;

determining a total shift for each of a plurality of pixels relative to the reference point of view using the processor configured by the image processing pipeline software, where the total shift of a given pixel location is the combination of a scene independent geometric correction determined for the given pixel location using geometric calibration data and the scene dependent geometric transformation determined for the given pixel location;

performing a super-resolution process utilizing at least a portion of plurality of input images and the total shift for each of the plurality of pixels relative to the reference point of view as inputs, where the super-resolution process comprises;

determining an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the input images using the processor configured by the image processing pipeline software based upon a total shift for each of the plurality of pixels relative to the reference point of view;

determining a high resolution image that when mapped through a forward imaging transformation matches the input images to within at least one predetermined criterion using the processor configured using the image processing pipeline software based upon the initial estimate of at least a portion of the high resolution image, where;

each forward imaging transformation corresponds to the manner in which each imager in the plurality of imagers captures the input images and comprises applying geometric transformations based upon the total shift at a given pixel location, which is the combination of a scene independent geometric correction determined for the given pixel location using geometric calibration data and the scene dependent geometric transformation determined for the given pixel location; and

the high resolution image has a resolution that is greater than any of the input images; and

generating a depth map for the high resolution image using a processor configured by image processing pipeline software by determining depth information for pixels in the high resolution image based upon the input images, parallax information, and the characteristics of the imager array;

determining a focus map for the high resolution image using the depth map using a processor configured by image processing pipeline software, where the focus map identifies pixels having depths in the depth map that are within a specified depth of a defined focal plane; and

performing dynamic refocus of the high-resolution image using a processor configured by image processing pipeline software by rendering the high resolution image using the focus map.