IP Library › Granted Patent US 12,456,176
Granted Patent B2
US 12,456,176 · App. 18/526,569 · Granted Oct 28, 2025

Image signal processor and noise removal method

Inventors: Chang Hun Cho (Icheon-si, KR); Ja Min Koo (Icheon-si, KR); Seung Hyun Kim (Icheon-si, KR); Tae Hyun Kim (Icheon-si, KR); Jae Hwan Jeon (Icheon-si, KR); Woo Young Jeong (Icheon-si, KR); Chang Hee Pyeoun (Icheon-si, KR)
Assignee: SK hynix Inc.
G06T5/70G06T7/20G06T7/50
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Quick Facts
Patent No.
US 12,456,176
App. No.
18/526,569
Granted
Oct 28, 2025
Kind
B2
Abstract

An image signal processor may include a data receiver configured to receive image data including depth values corresponding to pixels included in an image obtained from a distance measurement sensor. The image signal processor may also include a motion detector configured to detect motion in the image using either a first motion detection method which uses pixels or a second motion detection method which uses preset kernels, based on amplitude of the light source and generate a detection result indicating whether the motion is included in the target image. A noise remover removes noise from the target image using either a first noise removal method which uses previous image data corresponding to previous images or a second noise removal method which uses the image data corresponding to the target image based on the detection result.

Claims (60)

1. An image signal processor comprising:

a data receiver configured to receive image data including depth values respectively corresponding to pixels included in an image from a distance measurement sensor comprising a light source;

a motion detector configured to detect motion in a target image represented by the image data using one of a first motion detection method, which uses pixels and a second motion detection method that uses preset kernels, determined based on an amplitude of the light source, the motion detector additionally configured to generate a detection result indicating whether the motion is included in the target image; and

a noise remover configured to remove noise from the target image using one of a first noise removal method that uses previous image data corresponding to previous images generated before the target image is generated and a second noise removal method that uses only the image data corresponding to the target image, determined based on the detection result;

wherein the noise remover is configured to:

remove the noise using the first noise removal method responsive to the motion detection result indicating that the motion is not included in the target image or

remove the noise using the second noise removal method responsive to the motion detection result indicating that the motion is included in the target image.

2. The image signal processor according to claim 1 , wherein:

the motion detector is configured to detect the motion using the first motion detection method in response to the amplitude of the light source being greater than a preset amplitude threshold value, and

the first detection method determines whether the motion is included in the target image based on depth values of first pixels included in the previous images and depth values of second pixels included in the target image are generated.

3. The image signal processor according to claim 2 , wherein the motion detector is configured to calculate a depth value difference at a position of the target image based on the depth values of the first pixels and the depth values of the second pixels, and wherein the motion detector is configured to count a number of motion pixels for which the depth value difference is greater than a preset difference threshold value, and configured to generate a first detection result indicating that the motion is included in the target image in response to the number of motion pixels being greater than a preset motion threshold value.

4. The image signal processor according to claim 3 , wherein the motion detector is configured to generate a second detection result indicating that the motion is not included in the target image in response to the number of motion pixels being less than or equal to the preset motion threshold value.

5. The image signal processor according to claim 1 , wherein:

the motion detector is configured to detect the motion using the second motion detection method responsive to the amplitude of the light source being less than or equal to a preset amplitude threshold value, and

the second detection method determines whether the motion is included in the target image responsive to average depth values included in kernels set in the previous images.

6. The image signal processor according to claim 5 , wherein the motion detector is configured to calculate an average value difference between the kernels set at an identical position responsive to: the average depth values and motion kernels for which the average value difference is greater than a preset difference threshold value, the motion detector being additionally configured to generate a first detection result indicating that the motion is included in the target image when the number of motion kernels is greater than a preset motion threshold value.

7. The image signal processor according to claim 6 , wherein the motion detector is configured to generate a second detection result indicating that the motion is not included in the target image when the number of motion kernels is less than or equal to the preset motion threshold value.

8. The image signal processor according to claim 1 ,

wherein

the first noise removal method is obtaining a weighted sum of a depth value of the target image and depth values of the previous images corresponding to a position identical to that of the target image.

9. The image signal processor according to claim 1 ,

wherein

the second noise removal method is correcting a depth value of a noise pixel corresponding to the noise contained in the target image based on depth values of pixels neighboring the noise pixel.

10. A noise removal method in an image signal processor, the method comprising:

receiving image data including depth values respectively corresponding to pixels included in an image obtained from a distance measurement sensor, which uses a light source for modulating amplitude;

determining motion in a target image using at least one of: a first detection method that uses pixels based on an amplitude of the light source and a second detection method that uses preset kernels;

generating a detection result indicating whether the motion is included in the target image depending on the target motion detection method;

selecting, based on the detection result, a target noise removal method that is one of: a first noise removal method that uses previous image data corresponding to previous images generated before the target image is generated and a second noise removal method that uses only the image data corresponding to the target image; and

performing a noise removal operation depending on the target noise removal method:

wherein the determining the target noise removal method comprises:

selecting the first noise removal method responsive to the detection result indicating that the motion is not included in the target image or

selecting the second noise removal method as the target noise removal method in response to the detection result indicating that the motion is included in the target image.

11. The noise removal method according to claim 10 , wherein selecting the target motion detection method comprises:

determining the first detection method to be the target motion detection method in response to the amplitude of the light source being greater than a preset amplitude threshold value; and

generating the motion detection result comprises:

calculating a depth value difference at an identical position based on depth values of first pixels included in the previous images and depth values of second pixels included in the target image;

counting a number of motion pixels for which the depth value difference is greater than a preset difference threshold value; and

determining whether the motion is included in the target image based on the number of motion pixels.

12. The noise removal method according to claim 11 , wherein determining whether the motion is included in the target image comprises generating a first detection result indicating that the motion is included in the target image in response to the number of motion pixels being greater than a preset motion threshold value.

13. The noise removal method according to claim 11 , wherein determining whether the motion is included in the target image comprises generating a second detection result indicating that the motion is not included in the target image in response to the number of motion pixels being less than or equal to a preset motion threshold value.

14. The noise removal method according to claim 10 , wherein:

selecting the target motion detection method comprises:

selecting the second detection method in response to the amplitude of the light source being less than or equal to a preset amplitude threshold value, and generating the detection result comprises:

calculating an average value difference between kernels set at an identical position based on average depth values included in kernels set in the previous images and in the target image;

counting a number of motion kernels for which the average value difference is greater than a preset difference threshold value; and

determining whether the motion is included in the target image based on the number of motion kernels.

15. The noise removal method according to claim 14 , wherein determining whether the motion is included in the target image comprises generating a first detection result indicating that the motion is included in the target image when the number of motion kernels is greater than a preset motion threshold value.

16. The noise removal method according to claim 14 , wherein determining whether the motion is included in the target image comprises generating a second detection result indicating that the motion is not included in the target image when the number of motion kernels is less than or equal to a preset motion threshold value.

17. The noise removal method according to claim 10 ,

wherein

performing the noise removal operation comprises obtaining a weighted sum of a depth value of the target image and depth values of the previous images corresponding to a position identical to that of the target image.

18. The noise removal method according to claim 10 ,

wherein

performing the noise removal operation comprises correcting a depth value of a noise pixel corresponding to the noise contained in the target image based on depth values of pixels neighboring the noise pixel.

19. An image system comprising:

a distance measurement sensor comprising a light source and that is configured to generate image data including depth information using the light source; and

an image signal processor configured to remove noise contained in a current frame image based on the image data received from the distance measurement sensor:

wherein the image signal processor comprises:

a motion detector configured to detect motion in the current frame image using one of a first detection method that uses pixels based on strength of a signal generated by the light source and, a second detection method that uses preset kernels, and to generate a detection result indicating whether the motion is included in the current frame image depending on the target motion detection method; and

a noise remover configured to remove noise in the current frame image using one of a first noise removal method that uses previous image data corresponding to previous frames that precedes a current frame and a second noise removal method that uses only the image data corresponding to the current frame and to perform a noise removal operation depending on the target noise removal method.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 1, 2023
From: CHO, CHANG HUN; KOO, JA MIN; KIM, SEUNG HYUN; KIM, TAE HYUN; JEON, JAE HWAN; JEONG, WOO YOUNG; PYEOUN, CHANG HEE
To: SK HYNIX INC.
Reel/Frame 065735/0918 →
Priority Claims (1)
KR 10-2023-0077555 · Jun 16, 2023 · national
Continuity (1)
Related Publication 20240420289A1 · Dec 19, 2024
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