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    AI DOWNSCALING APPARATUS AND OPERATING METHOD THEREOF, AND AI UPSCALING APPARATUS AND OPERATING METHOD THEREOF
    1.
    发明公开
    AI DOWNSCALING APPARATUS AND OPERATING METHOD THEREOF, AND AI UPSCALING APPARATUS AND OPERATING METHOD THEREOF 审中-公开

    公开(公告)号：US20230177638A1

    公开(公告)日：2023-06-08

    申请号：US17312276

    申请日：2021-01-11

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Wookhyung KIM ,  Ilhyun CHO ,  Jayoon KOO ,  Namuk KIM

    IPC: G06T3/40 ,  G06V10/74 ,  G06V10/82

    CPC classification number: G06T3/4046 ,  G06T3/4053 ,  G06V10/761 ,  G06V10/82

    Abstract: An artificial intelligence (AI) upscaling apparatus for upscaling a low-resolution image to a high-resolution image includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to: obtain a second image corresponding to a first image, which is downscaled from an original image by an AI downscaling apparatus by using a first deep neural network (DNN); and obtain a third image by upscaling the second image by using a second DNN corresponding to the first DNN, and wherein the second DNN is trained to minimize a difference between a first restored image, which results from applying no pixel movement to an original training image, and second restored images, which result from downscaling, upscaling, and subsequently retranslating one or more translation images obtained by applying pixel movement to the original training image.

    AI DOWNSCALING APPARATUS AND OPERATING METHOD THEREOF, AND AI UPSCALING APPARATUS AND OPERATING METHOD THEREOF
    2.
    发明公开
    AI DOWNSCALING APPARATUS AND OPERATING METHOD THEREOF, AND AI UPSCALING APPARATUS AND OPERATING METHOD THEREOF 审中-公开

    公开(公告)号：US20240265493A1

    公开(公告)日：2024-08-08

    申请号：US18638310

    申请日：2024-04-17

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Wookhyung KIM ,  Ilhyun CHO ,  Jayoon KOO ,  Namuk KIM

    IPC: G06T3/4046 ,  G06T3/4053

    CPC classification number: G06T3/4046 ,  G06T3/4053

    Abstract: An artificial intelligence (AI) upscaling apparatus for upscaling a low-resolution image to a high-resolution image includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to: obtain a second image corresponding to a first image, which is downscaled from an original image by an AI downscaling apparatus by using a first deep neural network (DNN); and obtain a third image by upscaling the second image by using a second DNN corresponding to the first DNN, and wherein the second DNN is trained to minimize a difference between a first restored image, which results from applying no pixel movement to an original training image, and second restored images, which result from downscaling, upscaling, and subsequently retranslating one or more translation images obtained by applying pixel movement to the original training image.

    ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
    3.
    发明公开
    ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF 审中-公开

    公开(公告)号：US20240135697A1

    公开(公告)日：2024-04-25

    申请号：US18367193

    申请日：2023-09-11

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Ilhyun CHO ,  Wookhyung KIM ,  Jayoon KOO ,  Namuk KIM

    IPC: G06V10/82 ,  G06T3/40

    CPC classification number: G06V10/82 ,  G06T3/40

    Abstract: An electronic apparatus includes a memory configured to store a neural network model including a first network and a second network. The electronic apparatus also includes at least one processor connected to the memory. The at least one processor is configured to obtain description information corresponding to a first image by inputting the first image to the first network, obtain a second image based on the description information, obtain a third image representing a region of interest of the first image by inputting the first image and the second image to the second network. The neural network model is a model trained based on a plurality of sample images, a plurality of sample description information corresponding to the plurality of sample images, and a sample region of interest of the plurality of sample images.

    ELECTRONIC APPARATUS FOR EVALUATING QUALITY OF IMAGE AND OPERATING METHOD FOR THE SAME
    4.
    发明申请
    ELECTRONIC APPARATUS FOR EVALUATING QUALITY OF IMAGE AND OPERATING METHOD FOR THE SAME 有权

    公开(公告)号：US20240378714A1

    公开(公告)日：2024-11-14

    申请号：US18781512

    申请日：2024-07-23

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Wookhyung KIM ,  Jayoon KOO ,  Namuk KIM ,  Ilhyun CHO

    IPC: G06T7/00 ,  G06T5/20 ,  G06V10/771

    Abstract: Provided are an electronic apparatus for evaluating the quality of an image and an operating method of the electronic apparatus. The electronic apparatus includes a memory in which at least one instruction is stored and at least one processor configured to execute the at least one instruction stored in the memory to obtain the image, extract a feature map including a feature of the image based on the image, calculate a quality score for each reference region of the image based on the extracted feature map, calculate an importance for each reference region of the image based on the extracted feature map, and evaluate the quality of the image according to a final quality score of the image calculated based on the quality score for each reference region and the importance for each reference region.

    ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
    6.
    发明公开
    ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF 审中-公开

    公开(公告)号：US20240233356A9

    公开(公告)日：2024-07-11

    申请号：US18367193

    申请日：2023-09-12

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Ilhyun CHO ,  Wookhyung KIM ,  Jayoon KOO ,  Namuk KIM

    IPC: G06V10/82 ,  G06T3/40

    CPC classification number: G06V10/82 ,  G06T3/40

    Abstract: An electronic apparatus includes a memory configured to store a neural network model including a first network and a second network. The electronic apparatus also includes at least one processor connected to the memory. The at least one processor is configured to obtain description information corresponding to a first image by inputting the first image to the first network, obtain a second image based on the description information, obtain a third image representing a region of interest of the first image by inputting the first image and the second image to the second network. The neural network model is a model trained based on a plurality of sample images, a plurality of sample description information corresponding to the plurality of sample images, and a sample region of interest of the plurality of sample images.

    ELECTRONIC DEVICE FOR PERFORMING VIDEO QUALITY ASSESSMENT, AND OPERATION METHOD OF THE ELECTRONIC DEVICE
    7.
    发明申请
    ELECTRONIC DEVICE FOR PERFORMING VIDEO QUALITY ASSESSMENT, AND OPERATION METHOD OF THE ELECTRONIC DEVICE 有权

    公开(公告)号：US20220392210A1

    公开(公告)日：2022-12-08

    申请号：US17824587

    申请日：2022-05-25

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Wookhyung KIM ,  Anant BAIJAL ,  Cheulhee HAHM ,  Namuk KIM ,  Jayoon KOO ,  Ilhyun CHO

    IPC: G06V10/98 ,  G06V10/82 ,  G06V20/40 ,  G06N3/04

    Abstract: An electronic device is provided. The electronic device includes a memory storing one or more instructions, and a processor configured to execute the one or more instruction stored in the memory. The processor is configured to execute the one or more instructions to obtain a subjective assessment score for each of a plurality of sub-regions included in an input frame, the subjective assessment score being a Mean Opinion Score (MOS); obtain a location weight for each of the plurality of sub-regions, the location weight indicating characteristics according to a location of a display; obtain a weighted assessment score for each of the plurality of sub-regions, based on the subjective assessment score for each of the plurality of sub-regions and the location weight for each of the plurality of sub-regions; and obtain a final quality score for the entire video frame, based on the weighted assessment score for each of the plurality of sub-regions.

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