Capturing and processing of images including occlusions focused on an image sensor by a lens stack array
Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.
1. A depth-based image processing method that utilizes distance information determined using a plurality of images captured from different viewpoints, comprising:
normalizing, using at least one processor, a set of images captured by an imaging device based upon calibration data stored in a storage device, where the set of images comprises a plurality of images captured from different viewpoints;
measuring, using the at least one processor, parallax between the normalized set of images by:
performing pair-wise measurements between pixels from different images within the set of images to determine similarity of neighborhoods of pixels at different parallax shifts;
keeping a record of the pair-wise measurements and determining parallax shifts that yield the highest similarity between pixels within the set of images based upon the record of the pair-wise measurements; and
disregarding at least one determined parallax shift due to the impact of pixel occlusion;
generating, using the at least one processor, distance information based upon the measured parallax accounting for the viewpoints from which images within the set of images were captured;
processing, using the at least one processor, at least one image from the set of images using the distance information; and
displaying the at least one processed image on a display device.
2. The depth-based image processing method of claim 1 , wherein the imaging device comprises a camera array.
3. The depth-based image processing method of claim 2 , wherein the camera array comprises cameras having different fields of view.
4. The depth-based image processing method of claim 2 , wherein the display device is a 3D display device.
5. The depth-based image processing method of claim 1 , further comprising generating, using the at least one processor, a depth map based upon the distance information.
6. The depth-based image processing method of claim 5 , wherein processing the at least one image from the set of images using the distance information comprises reducing, using the at least one processor, the depth of field of at least one of the set of images based upon the depth map.
7. The depth-based image processing method of claim 5 , wherein processing the at least one image from the set of images using the distance information comprises:
receiving a selection of a focal plane distance at the at least one processor; and
applying, using the at least one processor, blurring to pixels within at least one image from the set of images based upon the selected focal plane distance and the depth map.
8. The depth-based image processing method of claim 5 , wherein processing the at least one image from the set of images using the distance information comprises applying, using the at least one processor, tone mapping to at least one image from the set of images based upon the depth map to guide the level of the tone mapping.
9. The depth-based image processing method of claim 5 , wherein the synthesizing the synthesized image further comprises applying, using the at least one processor, tone mapping to at least one image from the set of images based upon the depth map to guide the level of the tone mapping.
10. The depth-based image processing method of claim 1 , wherein:
the plurality of images have different occlusion sets; and
the occlusion set of a first image is the portion of a scene visible in a second image that is occluded in the first image.
11. The depth-based image processing method of claim 1 , wherein:
the set of images includes:
images captured using the same imaging characteristics; and
images captured using different imaging characteristics;
the pair-wise measurements between pixels from different images within the set of images are pair-wise measurements between pixels from images within the set of images captured using the same imaging characteristics.
12. The depth-based image processing method of claim 1 , wherein the pair-wise measurements between pixels from different images within the set of images comprise redundant pair-wise measurements to determine similarity of neighborhoods of pixels at different parallax shifts.
13. The depth-based image processing method of claim 1 , wherein the measured parallax is measured to detect sub-pixel offsets.
14. The depth-based image processing method of claim 13 , wherein performing pair-wise measurements between pixels from different images within the set of images to determine similarity of neighborhoods of pixels at different parallax shifts comprises performing pair-wise measurements between pixels from different images within the set of images at parallax shifts having sub-pixel offsets.
15. A depth-based image processing method that utilizes a depth map determined using a plurality of images captured from different viewpoints, comprising:
capturing a set of images using an imaging device comprising a camera array, where:
the set of images comprises a plurality of images that are captured from different viewpoints;
the plurality of images have different occlusion sets; and
the occlusion set of a first image is the portion of a scene visible in a second image that is occluded in the first image;
normalizing, using at least one processor, the set of images based upon calibration data stored in a storage device;
measuring, using the at least one processor, parallax between the normalized set of images with sub-pixel precision by:
performing redundant pair-wise measurements between pixels from different images within the set of images to determine similarity of neighborhoods of pixels at different parallax shifts including parallax shifts involving sub-pixel offsets;
keeping a record of the redundant pair-wise measurements and determining parallax shifts that yield the highest similarity between pixels within the set of images based upon the record of the redundant pair-wise measurements, where at least one determined parallax shift incorporates a sub-pixel offset; and
disregarding at least one determined parallax shift due to the impact of pixel occlusion;
generating, using the at least one processor, a depth map based upon the measured parallax accounting for the viewpoints from which images within the set of images were captured;
synthesizing an image, using at least one processor, based upon at least one image from the set of images and the depth map; and
displaying the synthesized image on a display device.
16. The depth-based image processing method of claim 15 , wherein the camera array comprises cameras having different fields of view.
17. The depth-based image processing method of claim 15 , wherein the display device is a 3D display device.
18. The depth-based image processing method of claim 15 , wherein the synthesized image is a reduced depth of field image and synthesizing the reduced depth of field image further comprises:
receiving a selection of a focal plane distance at the at least one processor; and
applying, using the at least one processor, blurring to pixels within at least one image from the set of images based upon the selected focal plane distance and the depth map.
19. The depth-based image processing method of claim 15 , wherein:
the set of images includes:
images captured using the same imaging characteristics; and
images captured using different imaging characteristics;
the pair-wise measurements between pixels from different images within the set of images are pair-wise measurements between pixels from images within the set of images captured using the same imaging characteristics.
20. A depth-based image processing method that utilizes distance information determined using a plurality of images captured from different viewpoints, comprising:
normalizing a set of images captured by an imaging device based upon calibration data, where the set of images comprises a plurality of images captured from different viewpoints;
measuring parallax between the normalized set of images by:
performing pair-wise measurements between pixels from different images within the set of images to determine similarity of neighborhoods of pixels at different parallax shifts;
keeping a record of the pair-wise measurements and determining parallax shifts that yield the highest similarity between pixels within the set of images based upon the record of the pair-wise measurements, where at least one determined parallax shift is disregarded due to the impact of pixel occlusion;
generating distance information based upon the measured parallax accounting for the viewpoints from which the images in the set of images were captured;
processing at least one image from the set of images using the distance information; and
displaying the at least one processed image on a display device.
21. The depth-based image processing method of claim 20 , wherein the imaging device comprises a camera array.
22. The depth-based image processing method of claim 21 , wherein the camera array comprises cameras having different fields of view.
23. The depth-based image processing method of claim 21 , wherein the display device is a 3D display device.
24. The depth-based image processing method of claim 20 , further comprising generating a depth map based upon the distance information.
25. The depth-based image processing method of claim 24 , wherein processing at least one image from the set of images using the distance information comprises reducing the depth of field of at least one of the set of images based upon the depth map.
26. The depth-based image processing method of claim 24 , wherein processing at least one image from the set of images using the distance information comprises:
selecting a focal plane distance; and
applying blurring to pixels within at least one image from the set of images based upon the selected focal plane distance and the depth map.
27. The depth-based image processing method of claim 24 , wherein processing at least one image from the set of images using the distance information comprises applying tone mapping to at least one image from the set of images based upon the depth map to guide the level of the tone mapping.
28. The depth-based image processing method of claim 20 , wherein:
the images in the plurality of images have different occlusion sets; and
the occlusion set of a first image is the portion of a scene visible in a second image that is occluded in the first image.
29. The depth-based image processing method of claim 20 , wherein the pair-wise measurements between pixels from different images within the set of images comprise redundant pair-wise measurements between to determine similarity of neighborhoods of pixels at different parallax shifts.
30. The depth-based image processing method of claim 29 , wherein the measured parallax is measured to detect sub-pixel offsets.