Method for image processing of high-bit depth sensors
High-bit depth sensors often capture more information then can be displayed on a commercially available display. Due to this, image processing systems and methods are disclosed to ensure that as much information as possible is presented to a user in a meaningful and statistically significant manner. The image processing systems and methods disclosed herein allow a user to view and process data that would otherwise be invisible to the user.
1. A method for processing an image comprising:
receiving an image from a high-bit sensor;
interpolating the image to its final output size;
globally processing the image and locally processing the image, wherein globally processing includes:
implementing Shannon-based entropy mapping if a number of unique values produced by the high-bit sensor exceeds the number of unique values that can be displayed in the final output size; and
implementing rank based mapping if a number of unique values produced by the high-bit sensor is lower than the number of unique values that can be displayed in the final output size;
weighting the globally processed image and the locally processed image;
combining the weighted images; and
outputting the image to a display wherein the weighted images are combined according to the equation ((WG*pixel value)+(WL*pixel value))/(WG+WL) where WG is weighting factor for the globally processed image and WL is weighting factor for the locally processed image.
2. The method of claim 1 , further comprising:
color enhancing the combined weighted image before outputting the image to the display.
3. The method of claim 2 , wherein the global processing and the local processing are performed in parallel.
4. The method of claim 1 , further comprising:
dynamically averaging the image wherein the image is a video image comprising consecutive frames.
5. The method of claim 4 , further comprising:
color enhancing the combined image before outputting the image to a display.
6. The method of claim 5 , wherein the global processing and the local processing are performed in parallel.
7. The method of claim 4 , wherein the dynamic averaging occurs on a pixel by pixel basis.
8. The method of claim 1 , wherein the global processing and the local processing are performed in parallel.
9. The method of claim 1 , wherein the local processing is a rank based processing.
10. The method of claim 1 , wherein the high-bit sensor is chosen from at least one of the following:
an x-ray camera, a high dynamic range monochromatic day camera, an image intensifier, and an infrared camera.
11. The method of claim 1 wherein the weighting factor for the globally processed image is greater than the weighting factor for the locally processed image.
12. The method of claim 1 wherein the weighting factor for the locally processed image is greater than the weighting factor for the globally processed image.
13. The method of claim 1 wherein the local processing utilizes a sliding pixel window.
14. The method of claim 13 wherein the sliding pixel window size is variable.
15. The method of claim 13 wherein the sliding pixel window size is user selectable.
16. The method of claim 13 wherein the sliding pixel window size is between 9×9 pixels and 25×25 pixels.
17. The method of claim 13 wherein the sliding pixel window size is about 25 pixels by 25 pixels.
18. A computer-implemented system, comprising:
one or more processors; and
one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including:
receiving an image from a high-bit sensor;
interpolating the image to its final output size;
globally processing the image and locally processing the image, wherein globally processing includes:
implementing Shannon-based entropy mapping if a number of unique values produced by the high-bit sensor exceeds the number of unique values that can be displayed in the final output size; and
implementing rank based mapping if a number of unique values produced by the high-bit sensor is lower than the number of unique values that can be displayed in the final output size;
weighting the globally processed image and the locally processed image;
combining the weighted images according to the equation ((WG*pixel value)+(WL*pixel value))/(WG+WL) where WG is weighting factor for the globally processed image and WL is weighting factor for the locally processed image; and outputting the image to a display.
19. The system of claim 18 , further comprising instructions configured to cause the one or more processors to perform operations including:
color enhancing the combined weighted image before outputting the image to the display.
20. The system of claim 19 , wherein the global processing and the local processing are performed in parallel.
21. The system of claim 18 , further comprising instructions configured to cause the one or more processors to perform operations including:
dynamically averaging the image wherein the image is a video image comprising consecutive frames.
22. The system of claim 21 , further comprising instructions configured to cause the one or more processors to perform operations including:
color enhancing the combined image before outputting the image to a display.
23. The system of claim 22 , wherein the global processing and the local processing are performed in parallel.
24. The system of claim 21 , wherein the dynamic averaging occurs on a pixel by pixel basis.
25. The system of claim 18 , wherein the global processing and the local processing are performed in parallel.
26. The system of claim 18 , wherein the local processing is a rank based processing.