Adaptive noise filter

• US 9,747,676 B2
• Filed: 03/21/2016
• Issued: 08/29/2017
• 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): PATEL, KANJIBHAI B
• Application Number:
  US15/076,477
• Publication Number:
  US 20160267633A1
• Time in Patent Office: 526 Days
• Field of Search: 382170, 382173
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20028 Bilateral filtering
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/11 Region-based segmentation

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 method for selecting a representative region of interest for an input image, the method comprising:

receiving an input image;

dividing the input image into a plurality of regions;

identifying one or more of the plurality of regions on which to perform a local analysis;

performing the local analysis on each of the one or more identified regions; and

selecting one of the one or more identified regions as a representative region based on results of the local analysis;

wherein the selecting one of the one or more identified regions as the representative region comprises;

for each of the one or more identified regions;

fitting a Gaussian curve to a histogram of pixel intensity values of the region,

determining whether a first percentage of all of the pixel intensity values in the region is accounted for in the histogram,

determining whether a second percentage of all of the pixel intensity values in the region is below or within the Gaussian curve in the histogram,

determining whether a third percentage of all of the pixel intensity values in the region is outside the Gaussian curve in the histogram;

assigning a quality score to each of the one or more identified regions; and

selecting one region as the representative region based on the quality scores.

2. A method according to claim 1, wherein the dividing the input image into the plurality of regions comprises superimposing a grid onto the input image.

3. A method according to claim 2, wherein the one or more identified regions comprises a plurality of regions proximal to a center of the grid.

4. A method according to claim 2, wherein the one or more identified regions comprises a plurality of regions proximal to outside edges of the grid.

5. A method according to claim 1, wherein the performing the local analysis on a region comprises fitting a Gaussian curve to a histogram of pixel intensity associated with the region.

6. A method according to claim 1 wherein the selecting one of the one or more identified regions as the representative region comprises calculating an intensity match ratio or a frequency match ratio.

7. A non-transitory computer readable medium storing code, which when executed by one or more processors cause the one or more processors to implement a method of selecting a representative region of interest for an input image, the code including instructions to:

receive an input image;

divide the input image into a plurality of regions;

identify one or more of the plurality of regions on which to perform a local analysis;

perform the local analysis on each of the one or more identified regions; and

select one of the one or more identified regions as a representative region based on results of the local analysis;

wherein the instructions to select one of the one or more identified regions as the representative region include instructions to;

for each of the one or more identified regions;

fit a Gaussian curve to a histogram of pixel intensity values of the region,

determine whether a first percentage of all of the pixel intensity values in the region is accounted for in the histogram,

determine whether a second percentage of all of the pixel intensity values in the region is below or within the Gaussian curve in the histogram,

determine whether a third percentage of all of the pixel intensity values in the region is outside the Gaussian curve in the histogram;

assign a quality score to each of the one or more identified regions; and

select one region as the representative region based on the quality scores.

8. The non-transitory computer readable medium of claim 7, wherein the instructions to divide the input image into the plurality of regions comprises instructions to superimpose a grid onto the input image.

9. The non-transitory computer readable medium of claim 8, wherein the one or more identified regions comprises a plurality of regions proximal to a center of the grid.

10. The non-transitory computer readable medium of claim 8 wherein the one or more identified regions comprises a plurality of regions proximal to outside edges of the grid.

11. The non-transitory computer readable medium of claim 7, wherein the instructions to perform the local analysis on a region comprises instructions to fit a Gaussian curve to a histogram of pixel intensity associated with the region.

12. The non-transitory computer readable medium of claim 7, wherein the instructions to select one of the one or more identified regions as the representative region comprises instructions to calculate an intensity match ratio or a frequency match ratio.