High linear dynamic range imaging
View Patent ↗A method for digital processing comprises receiving a first set of image data corresponding to a first time and a second set of image data corresponding to a different time. Intensity values for each of a first pixel and second pixel are extracted from each of the first and second set of image data. Substantially linear values in a plurality of intensity values are identified for each of the first and second pixels. For each of the first and second pixels, regression is performed on each of the substantially linear values in the plurality of intensity values. The regression may calculate an intensity level as a function of exposure time. The regression may generate slopes corresponding to the linear values for each of the first and second pixels. These slopes more accurately represent the actual ratio of intensity values. The ratios are useful in applications, such as, for example, polarization.
1. A method for processing digital image data, comprising:
receiving a plurality of sets of image data representing an image at different times;
extracting a first set of intensity values corresponding to a first pixel from the plurality of sets of image data, each set of image data having a corresponding time value, each intensity value in the first set being extracted from a corresponding set of image data;
identifying a first subset of the first set of intensity values excluding saturation and undercut data points, the intensity values of the first subset having a substantially linear relationship with each other;
performing regression on the first subset to generate a digital representation of the first pixel of the image, the regression deriving a first regression slope corresponding to the first pixel;
extracting a second set of intensity values corresponding to a second pixel from the plurality of sets of image data, each intensity value in the second set being extracted from a corresponding set of image data;
identifying a second subset of the second set of intensity values excluding saturation and undercut data points, the intensity values of the second subset having a substantially linear relationship with each other;
performing regression on the second subset to generate a digital representation of the second pixel of the image, the regression deriving a second regression slope corresponding to the second pixel; and
normalizing the first regression slope and the second regression slope by multiplying the first regression slope and the second regression slope by a normalizing value, the normalizing deriving a first relative intensity value corresponding to the first pixel and a second relative intensity value corresponding to the second pixel.
2. The method of claim 1 , further comprising:
storing the first regression slope and the second regression slope; and
storing the first relative intensity value and the second relative intensity value.
3. The method of claim 1 , further comprising:
spatially arranging the first pixel and the second pixel to create an image.
4. The method of claim 1 , wherein each time value corresponds to an exposure time for the corresponding set of image data.
5. The method of claim 1 , further comprising:
performing polarization calculations on the first regression slope and the second regression slope.
6. The method of claim 1 , wherein the first set of intensity values comprises one intensity value from each set of image data.
7. The method of claim 1 , further comprising:
receiving the plurality of sets of image data, the receiving of the plurality of sets of image data comprising receiving intensity values corresponding to a plurality of pixels defined for an image.
8. A data processing system, comprising:
a processor;
a memory communicatively coupled with the processor, the memory having instructions stored thereon that when executed by said processor cause said processor to perform the following:
receiving a plurality of sets of image data representing an image at different times;
extracting a first set of intensity values from the plurality of sets of image data, each set of image data having a corresponding time value, each intensity value in the first set being extracted from a corresponding set of image data, the first set of intensity values corresponding to a first pixel;
identifying a first subset of the first set of intensity values excluding saturation and undercut data points, the intensity values of the first subset having a substantially linear relationship with each other;
performing regression on the first subset to generate a digital representation of the first pixel of the image, the regression deriving a first regression slope corresponding to the first pixel;
extracting a second set of intensity values from the plurality of sets of image data, each intensity value in the second set being extracted from a corresponding set of image data, the second set of intensity values corresponding to a second pixel;
identifying a second subset of the second set of intensity values excluding saturation and undercut data points, the intensity values of the second subset having a substantially linear relationship with each other;
performing regression on the second subset to generate a digital representation of the second pixel of the image, the regression deriving a second regression slope corresponding to the second pixel; and
normalizing the first regression slope and the second regression slope by multiplying the first regression slope and the second regression slope by a normalizing value, the normalizing deriving a first relative intensity value corresponding to the first pixel and a second relative intensity value corresponding to the second pixel.
9. The system of claim 8 , the memory having further instructions stored thereon that when executed by said processor cause said processor to perform the following:
storing the first regression slope and the second regression slope; and
storing the first relative intensity value and the second relative intensity value.
10. The system of claim 8 , the memory having further instructions stored thereon that when executed by said processor cause said processor to perform the following:
spatially arranging the first pixel and the second pixel to create an image.
11. The system of claim 8 , wherein each time value corresponds to an exposure time for the image sensor.
12. The system of claim 8 , the memory having further instructions stored thereon that when executed by said processor cause said processor to perform the following:
performing polarization calculations on the first regression slope and the second regression slope.
13. The system of claim 8 , wherein the first set of intensity values comprises one intensity value from each set of image data.
14. The system of claim 8 , the memory having further instructions stored thereon that when executed by said processor cause said processor to perform the following:
receiving the plurality of sets of image data by receiving intensity values corresponding to a plurality of pixels defined for an image.
15. The system of claim 8 , further comprising an image sensor communicatively coupled with the processor, the image sensor adapted to capture image data.
16. The system of claim 15 , further comprising a lens communicatively coupled with the image sensor, the lens adapted to focus an image.
17. A method for processing data, comprising:
receiving values for a plurality of sensor outputs, the values corresponding to measurements taken at at least two points in time;
extracting a first set of values of said sensors outputs from the plurality of sensor outputs, the first set of values having a corresponding time value;
for each of the plurality of sensor outputs, deriving a regression slope for values in the first set of values that are substantially linear in a measuring range of the plurality of sensor outputs;
for each of the plurality of sensor outputs, storing the derived regression slope as a digital representation of the measurements at said at least two points in time; and
normalizing first and second regression slopes by multiplying the first regression slope and the second regression slope by a normalizing value, the normalizing deriving a first relative intensity value corresponding to a first pixel of the digital representation and a second relative intensity value corresponding to a second pixel of the digital representation.
18. The method of claim 17 , further comprising:
for each of the plurality of sensor outputs, normalizing the derived regression slope to derive a relative sensor output value; and
for each of the plurality of sensor outputs, storing the relative sensor output value.
19. The method of claim 18 , further comprising:
spatially arranging the plurality of sensor outputs, each having a relative sensor output value, the plurality of sensor outputs creating an image.
20. The method of claim 18 , wherein each point in time value corresponds to a measurement time for the plurality of sensor outputs.
21. The method of claim 17 , further comprising:
for each of the plurality of sensor outputs, performing polarization calculations on the derived regression slope.
22. The method of claim 17 , wherein receiving values for a plurality of sensor outputs comprises receiving sensor output values corresponding to a plurality of sensor outputs defined for an image.