US 12,277,503 B2
Image quality assessment using similar scenes as reference
Jinjun Wang, San Jose, CA (US); and Yudong Liang, Xi'an (CN)
Assigned to DeepNorth Inc., San Carlos, CA (US)
Filed by DeepNorth Inc., Redwood City, CA (US)
Filed on Oct. 16, 2023, as Appl. No. 18/487,676.
Application 18/487,676 is a continuation of application No. 17/380,699, filed on Jul. 20, 2021, granted, now 11,816,576.
Application 17/380,699 is a continuation of application No. 16/744,920, filed on Jan. 16, 2020, granted, now 11,100,402.
Application 16/744,920 is a continuation of application No. 15/792,546, filed on Oct. 24, 2017, granted, now 10,540,589.
Prior Publication US 2024/0046105 A1, Feb. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/00 (2017.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06N 3/084 (2023.01); G06T 7/33 (2017.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 10/98 (2022.01)
CPC G06N 3/084 (2013.01) [G06F 18/24133 (2023.01); G06N 3/045 (2023.01); G06T 7/0002 (2013.01); G06T 7/337 (2017.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 10/993 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30168 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A method to predict an image quality score associated with a plurality of images, the method comprising:
receiving, by a first deep path convolutional neural network, a set of reference images;
receiving, by a second deep path convolutional neural network, a set of distorted images, wherein each image in the set of distorted images is non-aligned with each image in the set of reference images;
extracting, by the first deep path convolutional neural network, a first set of one or more local features from the set of reference images;
extracting, by the second deep path convolutional neural network, a second set of one or more local features from the set of distorted images;
concatenating the first set of local features and the second set of local features;
generating an image quality assessment; and
predicting an image quality score.