Lensless imaging device
Technology is described for methods and systems for imaging an object ( 110 ). The method can include an image sensor ( 116 ) exposed to light ( 114 ) from an object ( 110 ) without passing the light through an image modification element. Light intensity of the light ( 114 ) can be stored as data in a medium. The image data can be analyzed at a processor ( 902 ) as a reconstructed image of the object ( 110 ).
1. A method for imaging an object, comprising:
exposing an image sensor to light from an object without passing the light through an image modification element;
recording light intensity from the light in a single capture and storing the light intensity as image data in a medium; and
reconstructing the image data as a reconstructed image of the object, wherein the image data is raw image data that is not focused through an image modification element, wherein the reconstructed image is a focused image of the object wherein the reconstructed image is a video.
2. The method of claim 1 , wherein the image sensor is a complementary metal-oxide-semiconductor (CMOS).
3. The method of claim 1 , wherein the step of reconstructing includes reconstructing the image data such that the reconstructed image is based on a reconstruction evaluation of the data combined with a space-variant point-spread function; and the method further comprises processing the reconstructed image at the processor with binary thresholding to form an image of the object.
4. The method of claim 1 , wherein a reconstruction evaluation for the reconstructed image employs a calibration matrix.
5. The method of claim 4 , wherein the calibration matrix includes at least one of varied wavelength data, varied light intensity, and varied distance.
6. The method of claim 1 , wherein the step of reconstructing includes applying deep learning on the image data such that the reconstructed image is a pattern recognition of an image characteristic of the image.
7. The method of claim 6 , wherein the image characteristic is at least one of color, facial recognition, motion, and shape.
8. The method of claim 1 , wherein the exposing the light from the object at the image sensor is between 10 ms and 100 ms.
9. The method of claim 1 , wherein a surface of the image sensor is engineered with scatterers.
10. The method of claim 1 , wherein the medium for the storing the light is local to the image sensor.
11. The method of claim 1 , wherein the medium for the storing the light is remote to the image sensor.
12. The method of claim 1 , wherein the image modification element is a lens or an aperture.
13. The method of claim 1 , wherein the light does not originate from a light source associated with the image sensor.
14. The method of claim 1 , wherein the light is not coherent light.
15. The method of claim 1 , wherein a distance between the object and the image sensor has a range of 85 to 497 millimeters.
16. A lensless imaging system for imaging an object, comprising:
an image sensor configured to be exposed to light from an object without passing the light through an image modification element;
a medium configured to record light intensity from the light in a single capture and store the light intensity as image data;
a processor configured to:
reconstructing the image data as a reconstructed image of the object, wherein the image data is raw image data that is not focused through an image modification element, wherein the reconstructed image is a focused image of the object wherein the reconstructed image is a video.
17. The imaging system of claim 16 , wherein the reconstructed image is based on a reconstruction evaluation of the data combined with a space-variant point-spread function; and the processor is further configured to process the reconstructed image at the processor with binary thresholding to form an image of the object.
18. The imaging system of claim 16 , wherein a reconstruction evaluation for the reconstructed image employs a calibration matrix.
19. The imaging system of claim 16 , wherein a different calibration matrix is employed for each distance between the object and the image sensor.
20. The imaging system of claim 16 , wherein the analyzing includes applying deep learning on the image data such that the reconstructed image is a pattern recognition of an image characteristic of the image.
21. The imaging system of claim 20 , wherein the image characteristic is at least one of color, facial recognition, motion, and shape.
22. The imaging system of claim 16 , wherein the image sensor is a complementary metal-oxide-semiconductor (CMOS).
23. The imaging system of claim 16 , wherein a surface of the image sensor is engineered with scatterers.
24. The imaging system of claim 16 , wherein the medium is local to the image sensor.
25. The imaging system of claim 16 , wherein a surface of the image sensor is covered with a coating that is at least partially transparent to the light and the coating does not focus the light onto the image sensor.
26. The imaging system of claim 16 , wherein the image modification element is a lens or an aperture.