Method of infrared image processing for non-uniformity correction

• US 10,015,425 B2
• Filed: 04/24/2015
• Issued: 07/03/2018
• Est. Priority Date: 04/30/2014
• Status: Active Grant

• Current Assignee: Lynred Co.
• Original Assignee: ULIS SAS (Thales SA)
• Inventors: Saragaglia, Amaury, Durand, Alain
• Primary Examiner(s): Vaughn, Jr., William C
• Assistant Examiner(s): Noh, Jae N
• Application Number:
  US14/695,539
• Publication Number:
  US 20150319387A1
• Time in Patent Office: 1,166 Days
• Field of Search: 348164
• CPC Class Codes: G01J 1/44 Electric circuits for command of an exposure part G03B7/02
• CPC Class Codes: G01J 2001/444 Compensating; Calibrating, e.g. dark current, temperature drift, noise reduction or baseline correction; Adjusting
• CPC Class Codes: G01J 5/22 Electrical features thereof
• CPC Class Codes: G01J 5/24 Use of specially adapted circuits, e.g. bridge circuits
• CPC Class Codes: H04N 25/67 applied to fixed-pattern noise, e.g. non-uniformity of response
• CPC Class Codes: H04N 25/671 for non-uniformity detection or correction
• CPC Class Codes: H04N 25/674 based on the scene itself, e.g. defocusing
• CPC Class Codes: H04N 3/09 for electromagnetic radiation in the invisible region, e.g. infrared
• CPC Class Codes: H04N 5/33 Transforming infrared radiation cameras or camera modules for generating image signals from infrared radiation H04N23/20; circuitry of SSIS for transforming infrared radiation into image signals H04N25/20

Abstract

The invention concerns a method of image processing involving: receiving, by a processing device, an input image (IB) captured by a pixel array sensitive to infrared radiation; determining, based on the input image and on a column component vector (VCOL), a first scale factor (α) by estimating a level of the column spread present in the input image; generating column offset values (α.VCOL(y)) based on the product of the first scale factor with the values of the vector; determining, based on the input image and on a 2D dispersion matrix (IDISP), a second scale factor (β) by estimating a level of the 2D dispersion present in the input image; generating pixel offset values (β.IDISP(x,y)) based on the product of the second scale factor with the values of the matrix; and generating a corrected image (IC′) by applying the column and pixel offset values.

Claims

1. A method of image processing comprising:

receiving, by a processing device, an input image captured by a pixel array sensitive to infrared radiation, the pixel array having a plurality of pixel columns, each pixel column being associated with a corresponding reference pixel;

determining, based on the input image and on a column component vector representing column spread introduced by the reference pixels, a first scale factor by estimating a level of said column spread present in the input image;

generating column offset values based on the product of the first scale factor with the values of said vector;

determining, based on the input image and on a 2D dispersion matrix representing 2D dispersion introduced by the pixel array, a second scale factor by estimating a level of said 2D dispersion present in the input image;

generating pixel offset values based on the product of the second scale factor with the values of said matrix; and

generating a corrected image by applying said column offset values and said pixel offset values.

2. The method of claim 1, further comprising generating a partially corrected image based on said column offset values, wherein said second scale factor is generated based on said partially corrected image.

3. The method of claim 1, wherein said column vector and dispersion matrix are determined based on a reference image representing offsets introduced by the pixel array and the associated reference pixels.

4. The method of claim 1, wherein said corrected image is generated based on the equation:

I_C′

=I_B(x,y)−

α

I_COL(x,y)−

β

I_DISP(x,y)

where I_B(x,y) is the input image, α

is the first scale factor, I_COL(x,y) is a matrix comprising in each of its rows the column vector, β

is the second scale factor, and I_DISP(x,y) is the dispersion matrix.

5. The method of claim 1, wherein:

the column vector (V_COL) represents the difference between a first column vector (I_COL^T0) based on a first reference image taken at a first ambient temperature (T0) and a second column vector (I_COL^T1) based on a second reference image taken at a second ambient temperature (T1);

the dispersion matrix (I_DISP) represents the difference between a first dispersion matrix (I_DISP^T0) based on said first reference image and a second dispersion matrix (I_DISP^T1) based on said second reference image.

6. The method of claim 5, wherein said corrected image (I_C′

) is generated based on the equation;

I_C′

=I_B(x,y)−

I_COL^T0(x,y)−

I_DISP^T0(x,y)−

α

(I_COL′

(x,y))−

β

(I_DISP′

(x,y))

where I_B(x,y) is the input image, α

is the first scale factor, I_COL^T0(x,y) is a matrix comprising in each of its rows the first column vector, I_COL′

(x,y) is a matrix equal to I_COL′

=(I_COL^T1−

I_COL^T0), where I_COL^T1 is a matrix comprising in each of its rows the second column vector, β

is the second scale factor, I_DISP^T0(x,y) is the first dispersion matrix and I_DISP′

(x,y) is a matrix equal to I_DISP′

=(I_DISP^T1−

I_DISP^T0), where I_DISP^T1 is the second dispersion matrix.

7. The method of claim 1, further comprising determining based on said corrected image (I_C′

) at least one column residue offset value.

8. The method of claim 7, wherein determining said at least one column residue offset value comprises:

determining weights associated with at least some of the pixels of said corrected image, the weights being generated based on an estimation of the uniformity of the neighborhood of each of said at least some pixels;

calculating, for each of the at least some pixels, the difference with respect to a pixel value in a corresponding row of an adjacent column; and

applying the weights to said differences and integrating the weighted differences to generate the at least one column residue offset value.

9. The method of claim 8, wherein the estimation of the uniformity of the neighborhood of each of said at least some pixels is based on a gradient value (P_x,y^∇

) and on a horizontal variance value (P_x,y^VAR) calculated for each neighborhood.

10. The method of claim 1, wherein determining the first scale factor comprises:

applying a high-pass filter along the rows of the image;

applying said high-pass filter to the column vector; and

determining column averages of the filtered image, wherein the first scale factor is determined based on a minimization of the differences between the column averages of the filtered image and the filtered values of the column vector.

11. The method of claim 1, wherein the first scale factor α

is determined based on the following equation;

12. The method of claim 1, wherein determining the second scale factor comprises:

determining, for each pixel of the input image and for each element of the dispersion matrix, a gradient value based on at least one adjacent pixel, wherein the second scale factor is determined based on a minimization of the difference between the gradients of the input image and the gradients of the dispersion matrix.

13. The method of claim 1, wherein the second scale factor β

is determined based on the following equation;

14. The method of claim 1, wherein said column and pixel offset values are applied to a further input image.

15. The method of claim 1, further comprising determining a gain correction value (γ

) by resolving the following minimization problem;

16. An image processing device comprising:

a processing device adapted to;

receive an input image captured by a pixel array sensitive to infrared radiation, the pixel array having a plurality of pixel columns, each pixel column being associated with a corresponding reference pixel;

determine, based on the input image and on a column vector representing column spread introduced by the reference pixels, a first scale factor by estimating a level of said column spread present in the input image;

generate column offset values based on the product of the first scale factor with the values of said column vector;

determine, based on the input image and on the dispersion matrix representing 2D dispersion introduced by the pixel array, a second scale factor by estimating a level of said 2D dispersion present in the input image;

generate pixel offset values based on the product of the second scale factor with the values of said matrix;

generate a corrected image by applying said column offset values and said pixel offset values; and

a memory storing the column vector and the dispersion matrix.