Systems and methods for synthesizing high resolution images using a set of geometrically registered images

• US 9,047,684 B2
• Filed: 10/21/2014
• Issued: 06/02/2015
• 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:
  US14/520,266
• Publication Number:
  US 20150042833A1
• Time in Patent Office: 224 Days
• Field of Search: 348/218.1, 348/335, 348/340, 250/208.1, 382/106, 382/276
• US Class Current: 1/1
• 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. An array camera, comprising:

an imager array including a plurality of imagers;

a processor; and

memory containing an image processing pipeline software application, an imaging prior including photometric calibration and geometric calibration data, and parameters defining a forward imaging transformation for the imager array;

wherein the image processing pipeline software directs the processor to;

trigger the imagers in the imager array to capture a plurality of images;

photometrically normalize each of the captured images using the photometric calibration data to obtain input images and storing the input images in memory;

applying scene independent geometric corrections to the input images using the geometric calibration data to obtain geometrically registered input images;

determine an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the geometrically registered input images; and

determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image.

2. The method of claim 1, wherein the image processing pipeline software directs the processor to photometrically normalize each of the captured images using the photometric calibration data to obtain input images by performing at least one photometric image processing process selected from the group consisting of:

photometric normalization;

Black Level calculation and adjustments;

vignetting correction; and

lateral color correction.

3. The method of claim 1, wherein the image processing pipeline software directs the processor to photometrically normalize each of the captured images using the photometric calibration data to obtain input images by performing temperature normalization.

4. The array camera of claim 1, wherein the imager array captures a single channel of information.

5. The array camera of claim 1, wherein the imager array captures three channels of information.

6. The array camera of claim 5, wherein the imager array includes imagers that sense red light (R), imagers that sense green light (G), and imagers that sense blue light (B).

7. The array camera of claim 1, wherein the imager array captures four channels of information.

8. The array camera of claim 7, wherein the four channels of information are the three RGB channels and a fourth near-IR channel.

9. The array camera of claim 8, wherein the imager array includes imagers that sense red light (R), imagers that sense green light (G), imagers that sense blue light (B), and imagers that sense near-IR wavelengths.

10. The array camera of claim 1, the image processing pipeline software directs the processor to encode the high resolution image in accordance with the JPEG standard.

11. The array camera of claim 10, wherein the image processing pipeline software directs the processor to store the encoded high resolution image in a file format selected from the group consisting of the JPEG Interchange Format (JIF), the JPEG File Interchange Format (JFIF), or the Exchangeable image file format (Exif).

12. The array camera of claim 1, wherein imagers in the plurality of imagers have different fields of view resulting in a change in magnification of the image captured by the underlying sensor of the imager.

13. The array camera of claim 1, wherein the image processing pipeline software directs the processor to generate a depth map for the high resolution image.

14. The array camera of claim 13, 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.

15. The array camera of claim 1, wherein the image processing pipeline software directs the processor to:

generate a focus map for the high resolution image; and

perform dynamic refocus of the high-resolution image by rendering the high resolution image using the focus map.

16. The array camera of claim 15, wherein the focus map identifies pixels having depths in the depth map that are within a specified depth of a defined focal plane.

17. The array camera 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.

18. The array camera of claim 17, wherein the image processing pipeline software further directs the processor to:

determine scene dependent parallax information with respect to the geometrically registered input images based upon disparity relative to a reference point of view resulting from the depths of points in the imaged scene, where the scene dependent parallax information comprises scene dependent geometric transformations; and

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 geometrically registered input images based upon scene dependent parallax information for each of the plurality of pixels relative to the reference point of view; and

wherein each forward imaging transformation comprises applying geometric transformations based upon scene dependent parallax information at a given pixel location, which is based upon the geometric transformation determined for the given pixel location.

19. The array camera of claim 18, 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.

20. The array camera of claim 18, wherein the image processing pipeline software directs the processor to determine an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the geometrically registered images by fusing at least portions of the geometrically registered input images to form the initial estimate of at least one portion of the high resolution image.

21. The array camera of claim 20, wherein the image processing pipeline software directs the processor to fuse at least portions of the input images to form the initial estimate of at least one portion of the high resolution image by:

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 geometrically registered input images using the scene dependent parallax information; and

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

22. The array camera of claim 18, wherein the image processing pipeline software directs the processor to determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image by:

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 geometrically registered input image; and

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

23. The array camera of claim 22, wherein the image processing pipeline software directs the processor to determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image by transforming, comparing and refining estimates until the at least one predetermined criterion is satisfied.

24. The array camera of claim 18, wherein the image processing pipeline software directs the processor to determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image by:

identifying pixels in the initial estimate of at least a portion of the high resolution image corresponding to pixels in at least one geometrically registered 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.

25. The array camera of claim 1, wherein the image processing pipeline software directs the processor to determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image by:

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.

26. The method of claim 1, wherein the imager array is an N×

M array of imagers.

27. The array camera 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.

28. An array camera, comprising:

an imager array including a plurality of imagers;

a processor; and

memory containing an image processing pipeline software application, an imaging prior including photometric calibration and geometric calibration data, and parameters defining a forward imaging transformation for the imager array;

wherein the image processing pipeline software directs the processor to;

trigger the imagers in the imager array to capture a plurality of images, where the captured 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; and

photometrically normalize each of the captured images using the photometric calibration data to obtain input images and storing the input images in memory;

applying scene independent geometric corrections to the input images using the geometric calibration data to obtain geometrically registered input images;

determine scene dependent parallax information with respect to the geometrically registered input images based upon disparity relative to a reference point of view resulting from the depths of points in the imaged scene, where the scene dependent parallax information comprises scene dependent geometric transformations;

determine an initial estimate of at least a portion of a high resolution image from a plurality of pixels from the geometrically registered input images based upon scene dependent parallax information for each of the plurality of pixels relative to the reference point of view, where the scene dependent parallax information of a given pixel location is the combination of a scene independent geometric correction determined for the given pixel using the scene dependent geometric transformation determined for the given pixel location; and

determine a high resolution image that when mapped through the forward imaging transformation matches the geometrically registered input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image;

wherein each forward imaging transformation corresponds to the manner in which each imager in the plurality of images captures the geometrically registered input images and comprises applying geometric transformations related to parallax observed due to the depths of points in the imaged scene; and

wherein the high resolution image has a resolution that is greater than any of the input images.