Image processing method, image processing apparatus, image processing system, and memory medium
An image processing method includes acquiring a captured image obtained by imaging, generating a first image by correcting a blur component of the captured image, and generating a second image based on the captured image, the first image, and weight information. The weight information is generated based on (i) information on brightness of the captured image or information on a scene of the captured image and (ii) information on a saturated area in the captured image.
1. An image processing method comprising:
acquiring a captured image obtained by imaging;
generating a first image by correcting a blur component of the captured image; and
generating a second image based on the captured image, the first image, and weight information,
wherein the weight information is generated based on (i) information on brightness of the captured image or information on a scene of the captured image and (ii) information on a saturated area in the captured image,
wherein the information on the saturated area is information indicating a relationship between (i) a range of an area in which an object in the saturated area has been spread by the blur component and (ii) a signal value corresponding to the area,
wherein the weight information is generated based on a third image obtained by a subtraction using the captured image and the information on the saturated area.
2. The image processing method according to claim 1 , wherein in generating the first image, the blur component is corrected by inputting the captured image into a machine learning model.
3. The image processing method according to claim 1 , wherein the information on the brightness of the captured image is a statistical amount relating to a signal value of the captured image.
4. The image processing method according to claim 3 , wherein the statistical amount is at least one of a mean value, a median value, a variance, and a histogram of the signal value.
5. The image processing method according to claim 1 , wherein the information on the scene of the captured image is information on a type of the scene of the captured image or information on an imaging mode used in the imaging.
6. The image processing method according to claim 1 , wherein the information on the saturated area is acquired by inputting the captured image into a machine learning model.
7. The image processing method according to claim 1 , wherein the information on the saturated area is acquired based on the saturated area and optical information on an optical system used in the imaging.
8. The image processing method according to claim 1 , wherein the weight information is generated based on a signal value of a pixel among a plurality of pixels in the third image, the pixel corresponding to a pixel in a non-saturated area in the captured image.
9. The image processing method according to claim 1 , wherein the weight information is generated based on a statistical amount relating to a signal value of each divided area in the third image.
10. The image processing method according to claim 1 , wherein as brightness of the third image increases, a weight of the captured image indicated by the weight information increases.
11. The image processing method according to claim 10 , wherein the brightness of the third image is determined based on a mean signal value of the third image.
12. The image processing method according to claim 1 , wherein as the brightness of the captured image increases, a weight of the captured image indicated by the weight information increases.
13. The image processing method according to claim 1 , wherein the blur component is based on optical information on an optical system used in the imaging.
14. The image processing method according to claim 1 , wherein in generating the second image, the second image is generated by obtaining a weighted mean of the captured image and the first image based on the weight information.
15. A non-transitory computer-readable memory medium storing a computer program that causes a computer to execute the image processing method according to claim 1 .
16. An image processing apparatus comprising at least one processor or circuit configured to execute a plurality of tasks including:
an acquiring task configured to acquire a captured image obtained by imaging;
a first generating task configured to generate a first image by correcting a blur component of the captured image; and
a second generating task configured to generate a second image based on the captured image, the first image, and weight information,
wherein the weight information is generated based on (i) information on brightness of the captured image or information on a scene of the captured image and (ii) information on a saturated area in the captured image,
wherein the information on the saturated area is information indicating a relationship between (i) a range of an area in which an object in the saturated area has been spread by the blur component and (ii) a signal value corresponding to the area, and
wherein the weight information is generated based on a third image obtained by a subtraction using the captured image and the information on the saturated area.
17. An image processing system comprising: the image processing apparatus according to claim 16 and a controlling apparatus communicable with the image processing apparatus,
wherein the controlling apparatus includes at least one processor or circuit configured to execute a plurality of tasks including a transmitting task configured to transmit, to the image processing apparatus, a request relating to execution of a process on a captured image obtained by imaging,
wherein the image processing apparatus includes at least one processor or circuit configured to execute a plurality of tasks including:
a receiving task configured to receive the request.
18. An image processing method comprising:
acquiring a captured image obtained by imaging;
generating a first image by correcting a blur component of the captured image; and
generating a second image based on the captured image, the first image, and weight information,
wherein the weight information is generated based on (i) information on brightness of the captured image or information on a scene of the captured image and (ii) information on a saturated area in the captured image,
wherein in generating the second image, the second image is generated by obtaining a weighted mean of the captured image and the first image based on the weight information.