System and methods for measuring depth using an array of independently controllable cameras

Patent metadata

Field	Value
Publication number	US-10909707-B2
Application number	US-201916537369-A
Country	US
Kind code	B2
Filing date	Aug 9, 2019
Priority date	Aug 21, 2012
Publication date	Feb 2, 2021
Grant date	Feb 2, 2021

Abstract

Systems in accordance with embodiments of the invention can perform parallax detection and correction in images captured using array cameras. Due to the different viewpoints of the cameras, parallax results in variations in the position of objects within the captured images of the scene. Methods in accordance with embodiments of the invention provide an accurate account of the pixel disparity due to parallax between the different cameras in the array, so that appropriate scene-dependent geometric shifts can be applied to the pixels of the captured images when performing super-resolution processing. In a number of embodiments, generating depth estimates considers the similarity of pixels in multiple spectral channels. In certain embodiments, generating depth estimates involves generating a confidence map indicating the reliability of depth estimates.

First claim

What is claimed is:

1. A method of synthesizing a higher resolution image from a set of lower resolution images captured from different viewpoints using at least one processor configured by an image processing application, the method comprising:
selecting a viewpoint of an image from the set of images captured from different viewpoints as a reference viewpoint;
normalizing the set of images to increase the similarity of corresponding pixels within the set of images;
determining depth estimates for pixel locations in an image from the reference viewpoint using at least a subset of the set of images;
determining the visibility of the pixels in the set of images from the reference viewpoint by comparing the photometric similarity of pixels from the set of images corresponding to a given pixel in the image from the set of images captured from the reference viewpoint, where pixels from the set of images that correspond to a given pixel are determined based upon the depth estimate determined for the given pixel; and
fusing pixels from the set of images based upon the depth estimates to create a fused image having a resolution that is greater than the resolutions of the images in the set of images by:
identifying the pixels from the set of images that are visible in an image from the reference viewpoint using the visibility information;
applying scene dependent geometric shifts to the pixels from the set of images that are visible in an image from the reference viewpoint to shift the pixels into the reference viewpoint, where the scene dependent geometric shifts are determined using the depth estimates; and
fusing the shifted pixels from the set of images to create a fused image from the reference viewpoint having a resolution that is greater than the resolutions of the images in the set of images.

2. The method of claim 1 , further comprising synthesizing an image from the reference viewpoint to perform a super-resolution process based upon the fused image from the reference viewpoint, the set of images captured from different viewpoints, the depth estimates, and the visibility information.

3. The method of claim 1 , wherein comparing the photometric similarity of pixels from the set of images corresponding to a given pixel in the image from the set of images captured from the reference viewpoint further comprises comparing the photometric similarity of pixels corresponding to a pixel in the image captured from the reference viewpoint.

4. The method of claim 3 , wherein photometric distance is used to determine photometric similarity.

5. The method of claim 3 , wherein pixels are considered visible when they have a threshold level of photometric similarity with the given pixel in the image from the set of images captured from the reference viewpoint.

6. The method of claim 5 , further comprising adapting the threshold based upon the similarity of the pixels in the set of images corresponding to the given pixel in the image from the set of images captured from the reference viewpoint.

7. The method of claim 5 , wherein the threshold is determined as a function of the photometric distance between the given pixel from the in the image from the set of images captured from the reference viewpoint and a corresponding pixel that is photometrically closest to the given pixel in the image from the set of images captured from the reference viewpoint.

8. The method of claim 5 , wherein the threshold is determined based upon the intensity of the given pixel in the image from the set of images captured from the reference viewpoint.

9. The method of claim 5 , wherein the threshold is determined based upon the average of a subset of pixel intensity values for corresponding pixels that are determined to be visible.

10. The method of claim 5 , wherein the threshold is determined using a signal to noise ratio value for the given pixel in the image from the set of images captured from the reference viewpoint.

11. The method of claim 5 , wherein the threshold is a fixed threshold.

12. The method of claim 1 , further comprising generating confidence metrics for the depth estimates for pixel locations in the image from the reference viewpoint, where a confidence metric for a given depth estimate for a pixel location in the image from the reference viewpoint encodes at least one confidence factor indicating the reliability of the given depth estimate.

13. The method of claim 12 , further comprising synthesizing an image from the reference viewpoint using the processor configured by the image processing application to perform a super-resolution process based upon the fused image from the reference viewpoint, the set of images captured from different viewpoints, the depth estimates, the visibility information, and the confidence metrics.

14. The method of claim 1 , wherein determining a depth estimate for a given pixel location in the image from the reference viewpoint comprises:
identifying pixels in the at least a subset of the set of images that correspond to the given pixel location in the image from the reference viewpoint based upon expected disparity at a plurality of depths;
comparing the similarity of the corresponding pixels identified at each of the plurality of depths; and
selecting the depth from the plurality of depths at which the identified corresponding pixels have the highest degree of similarity as a depth estimate for the given pixel location in the image from the reference viewpoint.

15. The method of claim 14 , wherein determining a depth estimate for a given pixel location in the image from the reference viewpoint further comprises:
determining an initial depth estimate for the pixel location in an image from the reference viewpoint based upon the disparity at which the identified corresponding pixels have the highest degree of similarity;
comparing the similarity of the identified corresponding pixels to detect mismatched pixels;
when an initial depth estimate does not result in the detection of a mismatch between the identified corresponding pixels, selecting the initial depth estimate as the depth estimate for the pixel location in the image from the reference viewpoint; and
when an initial depth estimate results in the detection of a mismatch between the identified corresponding pixels, updating the depth estimate for the pixel location in the image from the reference viewpoint by:
determining a set of candidate depth estimates using a plurality of competing subsets of the set of images based upon the disparities at which corresponding pixels have the highest degree of similarity in each of a plurality of competing subsets of images; and
selecting the candidate depth of the subset having the corresponding pixels with the highest degree of similarity as the updated depth estimate for the pixel location in the image from the reference viewpoint.

16. The method of claim 1 , wherein:
the images in the set of images are captured in multiple color channels;
determining depth estimates for pixel locations in an image from the reference viewpoint using at least a subset of the set of images comprises:
identifying pixels in the at least a subset of the set of images that correspond to the given pixel location in the image from the reference viewpoint based upon expected disparity at a plurality of depths;
in each of a plurality of color channels selected from the multiple color channels, comparing the similarity of the pixels that are identified as corresponding in the selected color channel at each of the plurality of depths; and
selecting the depth from the plurality of depths at which the

Assignees

• Fotonation Ltd

Inventors

• Ciurea Florian
• Venkataraman Kartik
• Molina Gabriel
• Lelescu Dan

Classifications

• H04N23/16

  Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction · CPC title

• G02B27/0075 Primary

  with means for altering, e.g. increasing, the depth of field or depth of focus · CPC title

• H04N13/243

  using three or more two-dimensional [2D] image sensors · CPC title

• H04N13/128

  Adjusting depth or disparity · CPC title

• H04N2013/0088

  Synthesising a monoscopic image signal from stereoscopic images, e.g. synthesising a panoramic or high resolution monoscopic image · CPC title