IP Library Granted Patent US 9,218,652
Granted Patent B2
US 9,218,652 · App. 14/444,425 · Granted Dec 22, 2015

Systems and methods for setting initial display settings

Inventor: Patrick G. Humphrey (Lincoln, NE)
Assignee: LI-COR, Inc.
G06T5/007G06T5/40G09G5/10G06T2207/20024G06T2207/20182G06T2207/20208G09G2320/029G09G2320/066G09G2320/08
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Quick Facts
Patent No.
US 9,218,652
App. No.
14/444,425
Granted
Dec 22, 2015
Kind
B2
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 (72)

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

receiving, by a processor of the display device, a data stream with data representing an image to be displayed;

filtering, by the processor, the data stream; and thereafter

determining, by the processor, a mean (μ) of a system background component of the data stream;

determining, by the processor, a standard deviation (σ) of a system background component of the data stream;

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

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

setting, by the processor, the display settings of the display device based on the display range.

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 , wherein filtering the data stream comprises:

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. A method according to claim 1 , further including displaying the image on the display device according to the display settings.

12. The method according to claim 1 , wherein filtering the data stream comprises:

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.

13. A method according to claim 12 , wherein the threshold percentage is 80%.

14. A computer readable medium storing code, which when executed by one or more processors of a display device cause the one or more processors to implement a method of setting display settings of the display device, the code including instructions that upon execution cause the one or more processors to:

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

filter the data stream; 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.

15. The computer-readable medium of claim 14 , 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.

16. The computer-readable medium of claim 14 , 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.

17. A computer-readable medium according to claim 16 , wherein the threshold percentage is 80%.

18. 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;

filtering the data stream; 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.

19. The system of claim 18 , further including a memory storing instructions, which when executed by the processor cause the processor to set or adjust the initial display settings.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 31, 2023
From: LI-COR, INC.
To: LI-COR BIOTECH, LLC
Reel/Frame 065410/0001 →
SECURITY INTEREST Recorded Oct 30, 2023
From: LI-COR BIOTECH, LLC
To: MIDCAP FINANCIAL TRUST
Reel/Frame 065396/0454 →
SECURITY INTEREST Recorded Dec 1, 2021
From: LI-COR, INC.
To: MIDCAP FINANCIAL TRUST
Reel/Frame 058293/0889 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 12, 2014
From: HUMPHREY, PATRICK G.
To: LI-COR, INC.
Reel/Frame 034155/0596 →
Continuity (2)
Provisional Application 61859110 · Jul 26, 2013
Related Publication 20150029207A1 · Jan 29, 2015