Image breathing correction systems and related methods

1. A method of correcting for breathing effects for images comprising:

providing a Field of View/Distortion (FOV/D) test image;

placing the FOV/D test image in the field of view of a lens comprised in a camera unit comprising an image sensor and a lens position sensor;

moving the lens to a first focus distance;

storing a first image of the FOV/D test image in a memory comprised in the camera unit using the image sensor;

determining a first lens position at the first focus distance using the lens position sensor;

generating a first calibrated Inverse FOV/D (IFOV/D) correction map by comparing FOV/D data of the first image with reference data associated with the FOV/D test image and stored in the memory using a processor comprised in the camera unit;

storing the first calibrated IFOV/D correction map in the memory;

moving the lens to a second focus distance;

storing a second image of the FOV/D test image in a memory included in the camera unit;

determining a second lens position at the second focus distance using the lens position sensor;

generating a second calibrated IFOV/D correction map by comparing FOV/D data of the second image with reference data associated with the FOV/D test image stored in the memory using the processor;

storing the second calibrated IFOV/D correction map in the memory,

wherein the first calibrated IFOV/D correction map and second calibrated IFOV/D correction map comprise a breathing correction model;

capturing a third image with the lens and the image sensor; and

applying the breathing correction model to the third image to generate a corrected third image, wherein breathing effects for the corrected third image are reduced.

2. The method of claim 1 , further comprising:

moving the lens to a third focus distance;

storing a third image of the FOV/D test image in the memory included in the camera unit;

determining a third lens position at the third focus distance using the lens position sensor;

generating a third calibrated IFOV/D correction map by comparing FOV/D data of the third image with reference data stored in the memory associated with the FOV/D test image using the processor;

storing the third calibrated IFOV/D correction map in the memory;

wherein the first calibrated IFOV/D correction map, second calibrated IFOV/D correction map, and third calibrated IFOV/D correction map comprise the breathing correction model.

3. The method of claim 1 , wherein the lens position sensor is a Hall Effect sensor.

4. The method of claim 1 , wherein the breathing correction model is stored in the memory in a look up table.

5. The method of claim 1 , wherein the FOV/D data of the first image and the FOV/D data of the second image are calculated using a distortion model that is one of 3rd order, 5th order, and arctangent/tangent.

6. A method of correcting for breathing effects for images comprising:

capturing and displaying a first image to a user using a lens, an image sensor, memory, and a display comprised in a camera unit;

adjusting a position of the lens;

capturing a second image with the lens and image sensor and storing data of the second image collected by the image sensor in the memory;

determining a second position of the lens at the time of the capturing of the second image using a lens position sensor included in the camera unit;

calculating an inverse Field of View/Distortion (IFOV/D) correction map for the second position of the lens using a processor comprised in the camera unit and a breathing correction model stored in the memory, wherein the breathing correction model stored in the memory is calculated with a Field of View/Distortion (FOV/D) test image;

applying the IFOV/D correction map to the data of the second image to generate corrected second image data using the processor;

storing the corrected second image data in the memory; and

displaying the corrected second image to a user using the display;

wherein the corrected second image is substantially free from breathing effects when compared with the first image.

7. The method of claim 6 , wherein the breathing correction model comprises at least a first calibrated IFOV/D correction map and a second calibrated IFOV/D correction map.

8. The method of claim 7 , wherein calculating the IFOV/D correction map for the second position of the lens further comprises interpolating the IFOV/D correction map using the second position of the lens and the at least first calibrated IFOV/D correction map and the second calibrated IFOV/D correction map.

9. The method of claim 7 , wherein FOV/D data used to generate the at least first calibrated IFOV/D correction map and the second calibrated IFOV/D correction map was calculated using a distortion model that is one of 3rd order, 5th order, and arctangent/tangent.

10. The method of claim 6 , wherein the breathing correction model is stored in a look up table.

11. The method of claim 6 , wherein the processor is a graphics processor unit (GPU).

12. The method of claim 6 , wherein the lens position sensor is a Hall Effect sensor.

13. A method of correcting for breathing effects for images comprising:

capturing and displaying a first image to a user using a lens, an image sensor, memory, and a display comprised in a camera unit;

adjusting a position of the lens;

capturing a second image with the lens and image sensor and storing data of the second image collected by the image sensor in the memory;

determining a second position of the lens at the time of the capturing of the second image using a lens position sensor included in the camera unit;

calculating a change in magnification from the first image to the second image for the second position of the lens using a processor comprised in the camera unit and a breathing correction model stored in the memory, wherein the breathing correction model stored in the memory is calculated with a Field of View/Distortion (FOV/D) test image;

resealing the data of the second image to generate corrected second image data using the processor;

storing the corrected second image data in the memory; and

displaying the corrected second image to a user using the display;

wherein the corrected second image is substantially free from breathing effects when compared with the first image.

14. The method of claim 13 , wherein the breathing correction model comprises at least a first calibrated IFOV/D correction map and a second calibrated IFOV/D correction map.

15. The method of claim 14 , wherein calculating a change in magnification from the first image to the second image further comprises interpolating an IFOV/D correction map using the second position of the lens and the at least first calibrated IFOV/D correction map and the second calibrated IFOV/D correction map.

16. The method of claim 14 , wherein FOV/D data used to generate the at least first calibrated IFOV/D correction map and the second calibrated IFOV/D correction map was calculated using a distortion model that is one of 3rd order, 5th order, and arctangent/tangent.

17. The method of claim 13 , wherein the breathing correction model is stored in a look up table.

18. The method of claim 13 , wherein the processor is a graphics processor unit (GPU).

19. The method of claim 13 , wherein the lens position sensor is a Hall Effect sensor.