Data processing device and method for correcting image shading

Patent metadata

Field	Value
Publication number	US-2025022102-A1
Application number	US-202418768102-A
Country	US
Kind code	A1
Filing date	Jul 10, 2024
Priority date	Jul 10, 2023
Publication date	Jan 16, 2025
Grant date	—

Abstract

The invention relates to a data processing device for an imaging apparatus, the device being configured to obtain a length threshold value, to access input image data representing at least one digital input image, wherein the input image data comprise a shading signal representing a brightness decrease towards the edges of the at least one digital input image, and a content signal representing image features of the at least one digital input image, the image features having a length that is smaller than the length threshold value, to compute a baseline image based on the input image data and the length threshold value, wherein the baseline image is representative of an estimate of the shading signal, to generate at least one digital output image representative of an estimate of the content signal by at least one of a) subtracting the baseline image from the input image data and b) dividing the input image data by the baseline image. Advantageously, the data processing device allows a shading correction without the need for obtaining any separate background image or reducing the image size. The invention also relates to a computer-implemented method and a method for operating such an imaging apparatus. Further, the invention relates to a computer program and a computer-readable medium. Lastly, the invention relates to a neural network device trained by means of the data processing device or the computer-implemented method.

First claim

1 . A data processing device for an imaging apparatus, the device being configured:
to obtain a length threshold value, to access input image data representing at least one digital input image, wherein the input image data comprise
a shading signal representing a brightness decrease towards the edges of the at least one digital input image, and
a content signal representing image features of the at least one digital input image, the image features having a length that is smaller than the length threshold value,
to compute a baseline image based on the input image data and the length threshold value, wherein the baseline image is representative of an estimate of the shading signal, to generate at least one digital output image representative of an estimate of the content signal by at least one of
subtracting the baseline image from the input image data and
dividing the input image data by the baseline image.

2 . The data processing device according to claim 1 , wherein the at least one digital input image is a photon count image and the at least one digital output image is generated by dividing the input image data by the baseline image.

3 . The data processing device according to claim 1 , wherein the length threshold value depends on a size of the at least one digital input image.

4 . The data processing device according to claim 1 , wherein the device is configured to compute the baseline image using a fit to the input image data, and wherein the fit is calculated by an iterative minimization scheme.

5 . The data processing device according to claim 4 , wherein the iterative minimization scheme comprises a least-square minimization criterion, which is to be minimized for the fit, wherein the least-square minimization criterion comprises a penalty term and a cost function.

6 . The data processing device according to claim 5 , wherein the penalty term includes a derivative of the baseline image.

7 . The data processing device according to claim 5 , wherein the cost function represents a difference between the input image data and the baseline image.

8 . The data processing device according to claim 5 , wherein the iterative minimization scheme comprises a first iterative stage and a second iterative stage, wherein,
in the first iterative stage auxiliary data are updated depending on the baseline image of a previous iteration, a truncated quadratic term and the input image data and, in the second iterative stage, the baseline image is computed using a convolution of a discrete Green's function with a sum of the input image data and the updated auxiliary data.

9 . The data processing device according to claim 1 , wherein the input image data represent multiple digital input images.

10 . The data processing device according to claim 9 , wherein the device is configured
to compute the baseline image for each of the multiple digital input images, and to calculate an averaged baseline image based on the baseline images of the multiple digital input images.

11 . The data processing device according to claim 10 , wherein the device is configured to generate multiple digital output images by at least one of
subtracting the averaged baseline image from the input image data and dividing the input image data by the averaged baseline image.

12 . The data processing device according to claim 9 , wherein the device is configured:
to calculate averaged input image data from the multiple digital input images, to compute an averaged baseline image based on the averaged input image data and the length threshold value, and to generate multiple digital output images by at least one of
subtracting the averaged baseline image from the input image data and
dividing the input image data by the averaged baseline image.

13 . An imaging apparatus comprising a data processing device according to claim 1 ,
wherein the apparatus is configured to record the input image data representing the at least one digital input image.

14 . A computer-implemented method for processing input image data of an imaging apparatus, the method comprising the steps of:
obtaining a length threshold value, accessing input image data representing at least one digital input image, wherein the input image data comprise
a shading signal representing a brightness decrease towards the edges of the at least one digital input image, and
a content signal representing image features of the at least one digital input image, the image features having a length that is smaller than the length threshold value,
computing a baseline image based on the input image data and the length threshold value, wherein the baseline image is representative of an estimate of the shading signal, generating at least one digital output image representative of an estimate of the content signal by at least one of
subtracting the baseline image from the input image data and
dividing the input image data by the baseline image.

15 . A method for operating an imaging apparatus, the method comprising the steps of:
recording input image data representing at least one digital input image, and carrying out the computer-implemented method according to claim 14 .

16 . A non-transitory, computer-readable medium comprising a program code that, when the program code is executed on a processor, a computer, or a programmable hardware component, causes the processor, computer, or programmable hardware component to perform the method of claim 14 .

17 . A neural network device trained by a plurality of digital input images and a plurality of digital output images, where the digital output images are computed from the digital input images with the data processing device according to claim 1 .

Assignees

• Leica Microsystems

Inventors

• Schlicker Oliver
• Schechter Markus
• Walter Kai

Classifications

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/10056

  Microscopic image · CPC title

• G06T5/50 Primary

  using two or more images, e.g. averaging or subtraction · CPC title

• G06T5/80

  Geometric correction · CPC title