Systems and methods for setting initial display settings

• US 9,953,404 B2
• Filed: 12/17/2015
• Issued: 04/24/2018
• Est. Priority Date: 07/26/2013
• Status: Active Grant

• Current Assignee: Li-Cor Biotech LLC
• Original Assignee: Li & S Company Limited (Yesco Holdings Co., Ltd.)
• Inventors: Humphrey, Patrick G.
• Primary Examiner(s): Caschera, Antonio A
• Application Number:
  US14/973,328
• Publication Number:
  US 20160104271A1
• Time in Patent Office: 859 Days
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: G06T 2207/20028 Bilateral filtering
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20208 High dynamic range [HDR] image processing
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof
• CPC Class Codes: G06T 5/94 based on local image properties, e.g. for local contrast enhancement
• CPC Class Codes: G09G 2320/029 by monitoring one or more pixels in the display panel, e.g. by monitoring a fixed reference pixel
• CPC Class Codes: G09G 2320/066 for control of contrast
• CPC Class Codes: G09G 2320/08 Arrangements within a display terminal for setting, manually or automatically, display parameters of the display terminal
• CPC Class Codes: G09G 5/10 Intensity circuits

Abstract

A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.

Claims

1. A processor-implemented method for setting display settings of a display device, the method comprising:

a) receiving, by a processor, a data stream with data representing an image to be displayed;

and thereafter

b) determining, by the processor, a mean (μ

) of a system background component of the data stream;

c) determining, by the processor, a standard deviation (σ

) of a system background component of the data stream;

d) identifying, by the processor, a multiplier value (M);

e) calculating, by the processor, a display range of the image to be displayed based on the mean, the standard deviation, and the multiplier value;

f) setting the display settings of the display device based on the display range; and

g) displaying the data stream on the display device according to the display settings.

2. The method according to claim 1, wherein the multiplier value is preconfigured.

3. The method according to claim 1, wherein the multiplier value is 100.

4. The method according to claim 1, wherein the multiplier value is adjustable.

5. The method according to claim 1, wherein calculating a display range comprises calculating:

μ

+(M*σ

).

6. The method according to claim 1, further including filtering the data stream by:

selecting a first region of the image to be displayed;

generating an initial histogram of pixel intensity values in the first region, wherein the histogram includes a plurality of bins;

identifying a first bin as a bin having a greatest count of pixel intensity values;

identifying a left bin as a closest bin to the left of the first bin in the histogram that has a count that is less than a first count percentage of the greatest count;

identifying a right bin as a closest bin to the right of the first bin in the histogram that has a count that is less than a second count percentage of the greatest count;

generating an updated histogram of pixel intensity values having a range between the identified left bin and identified right bin;

fitting a Gaussian curve onto the updated histogram; and

applying a filter to the image based on parameters of the Gaussian curve.

7. A method according to claim 6, wherein the first count percentage and the second count percentage are 2%.

8. A method according to claim 6, wherein the filter is a bilateral filter.

9. A method according to claim 6, wherein edges of the updated histogram are within a threshold percentage of the range of the pixel intensity values between the identified left bin and identified right bin.

10. A method according to claim 9, wherein the threshold percentage is 80%.

11. The method of claim 1, wherein the data stream comprises data representing multiple images and wherein steps b)-f) are performed for each of the multiple images in the data stream.

12. The method of claim 1, wherein the data stream comprises data representing multiple images and wherein steps b)-f) are performed only once for all of the multiple images in the data stream.

13. The method according to claim 1, further including filtering the data stream by:

selecting a first region of the image to be displayed;

generating an initial histogram of pixel intensity values in the first region, wherein the histogram includes a plurality of bins; and

a) identifying a first bin as a bin having a greatest count of pixel intensity values;

b) identifying a left bin as a closest bin to the left of the first bin in the histogram that has a count that is less than a first count percentage of the greatest count;

c) identifying a right bin as a closest bin to the right of the first bin in the histogram that has a count that is less than a second count percentage of the greatest count; and

d) determining whether edges of the histogram are within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, and

i) if edges of the histogram are within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, fitting a Gaussian curve onto the histogram, and applying a filter to the image based on parameters of the Gaussian curve; and

ii) if edges of the histogram are not within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, generating an updated histogram of pixel intensity values having a range between the identified left bin and identified right bin, and repeating steps a)-d) using the updated histogram.

14. A method according to claim 13, wherein the threshold percentage is 80%.

15. A display device comprising one or more processors and a memory storing code, which when executed by the one or more processors cause the one or more processors to implement a method of setting display settings of the display device, the code including instructions to:

receive a data stream with data representing an image to be displayed;

and thereafter

determine a mean (μ

) of a system background component of the data stream;

determine a standard deviation (σ

) of a system background component of the data stream;

identify a multiplier value (M);

calculate a display range of the image to be displayed based on the mean, the standard deviation, and the multiplier value; and

set the display settings of the display device based on the display range.

16. The display device of claim 15, wherein the code further includes instructions to filter the data stream, wherein the instructions to filter the data stream include instructions to:

select a first region of the image to be displayed;

generate an initial histogram of pixel intensity values in the first region, wherein the histogram includes a plurality of bins;

identify a first bin as a bin having a greatest count of pixel intensity values;

identify a left bin as a closest bin to the left of the first bin in the histogram that has a count that is less than a first count percentage of the greatest count;

identify a right bin as a closest bin to the right of the first bin in the histogram that has a count that is less than a second count percentage of the greatest count;

generate an updated histogram of pixel intensity values having a range between the identified left bin and identified right bin;

fit a Gaussian curve onto the updated histogram; and

apply a filter to the image based on parameters of the Gaussian curve.

17. The display device of claim 15, wherein the code further includes instructions to filter the data stream, wherein the instructions to filter the data stream include instructions to:

select a first region of the image to be displayed;

generate an initial histogram of pixel intensity values in the first region, wherein the histogram includes a plurality of bins; and

a) identify a first bin as a bin having a greatest count of pixel intensity values;

b) identify a left bin as a closest bin to the left of the first bin in the histogram that has a count that is less than a first count percentage of the greatest count;

c) identify a right bin as a closest bin to the right of the first bin in the histogram that has a count that is less than a second count percentage of the greatest count; and

d) determine whether edges of the histogram are within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, and

i) if edges of the histogram are within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, fit a Gaussian curve onto the histogram, and apply a filter to the image based on parameters of the Gaussian curve; and

ii) if edges of the histogram are not within a threshold percentage of the range of pixel intensity values between the identified left bin and identified right bin, generate an updated histogram of pixel intensity values having a range between the identified left bin and identified right bin, and repeating steps a)-d) using the updated histogram.

18. A display device according to claim 17, wherein the threshold percentage is 80%.

19. An image display system, comprising:

a display device, and a processor coupled with the display device, wherein the processor is configured to set or adjust initial display settings of the display device by;

receiving a data stream with data representing an image to be displayed;

and thereafter

determining a mean (μ

) of a system background component of the data stream;

determining a standard deviation (σ

) of a system background component of the data stream;

identifying a multiplier value (M);

calculating a display range of the image to be displayed based on the mean, the standard deviation, and the multiplier value; and

setting one or more display settings of the display device based on the display range.

20. The system of claim 19, further including a memory storing instructions, which when executed by the processor cause the processor to set or adjust the initial display settings.

21. The system of claim 19, wherein the processor is further configured to, prior to the determining the mean (μ

) of a system background component of the data stream, filter the data stream.