Reduced Hardware Implementation For A Two-Picture Depth Map Algorithm

• US 20090268985A1
• Filed: 04/29/2008
• Published: 10/29/2009
• Est. Priority Date: 04/29/2008
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Inventors: Li, Pingshan, Murakami, Yoshihiro, Nakamura, Makibi, Wong, Earl Quong, Kushida, Hidenori, Triteyaprasert, Soroj
• Granted Patent: US 8,280,194 B2
• Time in Patent Office: Days
• US Class Current: 382/299
• CPC Class Codes: G02B 27/0075 with means for altering, e.g. increasing, the depth of field or depth of focus
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 7/571 from focus
• CPC Class Codes: G06V 10/147 Details of sensors, e.g. sensor lenses fingerprint or palmprint sensors G06V40/13; vascular sensors G06V40/145; eye sensors G06V40/19
• CPC Class Codes: G06V 2201/12 Acquisition of 3D measurements of objects

Abstract

An imaging system generates a picture depth map from a pair of reduced resolution images. The system captures two full resolution images, receives image reduction image information and creates two reduced resolution images. The system computes a blur difference between the two reduced resolution images at different image locations. The system calculates the depth map based on the blur difference between the two reduced resolution images at different image locations.

Claims

1. A computerized method comprising:

generating a first and second reduced resolution image using reduction information for the first and second reduced resolution image;

computing a blur difference in the first and a second reduced resolution image; and

calculating a depth map based on the blur difference of the first and second reduced resolution images.

2. The computerized method of claim 1, wherein each pixel of the first reduced image comprises averaging a block of pixels from a full resolution image.

3. The computerized method of claim 2, wherein the averaging is calculated from one of full color pixel information and one color channel pixel information.

4. The computerized method of claim 1, wherein the blur difference is larger than a pixel size of the first reduced resolution image and second reduced resolution images.

5. The computerized method of claim 1, wherein the image reduction information is a factor used to reduce the image dimensions.

6. The computerized method of claim 5, wherein image reduction information factor is a factor k.

7. The computerized method of claim 1, wherein the first reduced resolution image has a same aspect ratio as a full resolution image.

8. The computerized method of claim 1, wherein the calculating the depth simulates a Gaussian blur with a convolving kernel related to a pillbox blur quantity.

9. The computerized method of claim 1, wherein the generating the first and second reduced resolution images is based on a first and second full resolution images, wherein the first and second full resolution images were acquired with a separation of more than one depth of field.

10. A machine readable medium having executable instructions to cause a processor to perform a method comprising:

generating a first and second reduced resolution image using reduction information for the first and second reduced resolution image;

computing a blur difference in the first and a second reduced resolution image; and

calculating a depth map based on the blur difference of the first and second reduced resolution images.

11. The machine readable medium of claim 10, wherein each pixel of the first reduced image comprises averaging a block of pixels from a full resolution image.

12. The machine readable medium of claim 11, wherein the averaging is calculated from one of full color pixel information and one color channel pixel information.

13. The machine readable medium of claim 10, wherein the blur difference is larger than a pixel size of the first reduced resolution image and second reduced resolution images.

14. The machine readable medium of claim 10, wherein the image reduction information is a factor used to reduce the image dimensions.

15. The machine readable medium of claim 14, wherein image reduction information factor is a factor k.

16. The machine readable medium of claim 10, wherein the first reduced resolution image has a same aspect ratio as a full resolution image.

17. The machine readable medium of claim 10, wherein the calculating the depth simulates a Gaussian blur with a convolving kernel related to a pillbox blur quantity.

18. An apparatus comprising:

means for generating a first and second reduced resolution image using reduction information for the first and second reduced resolution image;

means for computing a blur difference in the first and a second reduced resolution image; and

means for calculating a depth map based on the blur difference of the first and second reduced resolution images.

19. The apparatus of claim 18, wherein each pixel of the first reduced image comprises averaging a block of pixels from a full resolution image.

20. A system comprising:

a processor;

a memory coupled to the processor though a bus; and

a process executed from the memory by the processor to cause the processor to generate a first and second reduced resolution image using reduction information for the first and second reduced resolution image, compute a blur difference in the first and a second reduced resolution image, and to calculate a depth map based on the blur difference of the first and second reduced resolution images