IMAGE PROCESSING APPARATUS AND OPERATION METHOD THEREOF

    公开(公告)号:US20220245767A1

    公开(公告)日:2022-08-04

    申请号:US17573010

    申请日:2022-01-11

    Abstract: An image processing apparatus includes: a memory storing one or more instructions; and a processor by executing the one or more instructions stored in the memory is configured to: extract a first image feature from a first image; search for, based on a transmission characteristic of the first image and the first image feature, a first cluster corresponding to the first image from among a plurality of clusters stored in the image processing apparatus, each cluster including a representative image feature and a representative image quality parameter; perform image quality processing on the first image based on a first representative image quality parameter in the first cluster; obtain, based on the first image that has undergone the image quality processing, a first update parameter obtained by updating the first representative image quality parameter; and update the plurality of clusters based on the first update parameter.

    AI ENCODING APPARATUS AND OPERATION METHOD OF THE SAME, AND AI DECODING APPARATUS AND OPERATION METHOD OF THE SAME

    公开(公告)号:US20240378761A1

    公开(公告)日:2024-11-14

    申请号:US18781478

    申请日:2024-07-23

    Abstract: An artificial intelligence (AI) encoding apparatus includes at least one processor configured to: determine a downscaling target, based on a target resolution for a first image, obtain the first image by AI-downscaling an original image using an AI-downscaling neural network corresponding to the downscaling target, generate image data by encoding the first image, select AI-upscaling neural network set identification information, based on the target resolution of the first image, characteristic information of the original image, and a target detail intensity, generate AI data including the target resolution of the first image, bit depth information of the first image, the AI-upscaling neural network set identification information, and encoding control information, and generate AI encoding data including the image data and the AI data; and a communication interface configured to transmit the AI encoding data to an AI decoding apparatus, wherein the AI data includes information about an AI-upscaling neural network corresponding to the AI-downscaling neural network.

    ELECTRONIC APPARATUS, CONTROL METHOD THEREOF AND ELECTRONIC SYSTEM

    公开(公告)号:US20220414828A1

    公开(公告)日:2022-12-29

    申请号:US17902775

    申请日:2022-09-02

    Abstract: An electronic apparatus includes a memory configured to store a downscaling network of a first artificial intelligene model, a communication interface comprising communication circuitry, and a processor connected to the memory and the communication interface and configured to control the electronic apparatus, wherein the processor is configured to: obtain an output image in which an input image is downscaled by inputting the input image the downscaling network, control the communication interface to transmit the output image to another electronic apparatus, and wherein the first artificial intelligene model is configured to be learned based on: a sample image, a first intermediate image obtained by inputting the sample image to the downscaling network, a first final image obtained by inputting the first intermediate image to an upscaling network of the first artificial intelligene model, a second intermediate image in which the sample image is downscaled by a legacy scaler, and a second final image in which the first intermediate image is upscaled by the legacy scaler.

    AI ENCODING APPARATUS AND OPERATION METHOD OF THE SAME, AND AI DECODING APPARATUS AND OPERATION METHOD OF THE SAME

    公开(公告)号:US20220180568A1

    公开(公告)日:2022-06-09

    申请号:US17522579

    申请日:2021-11-09

    Abstract: An artificial intelligence (AI) encoding apparatus includes at least one processor configured to: determine a downscaling target, based on a target resolution for a first image, obtain the first image by AI-downscaling an original image using an AI-downscaling neural network corresponding to the downscaling target, generate image data by encoding the first image, select AI-upscaling neural network set identification information, based on the target resolution of the first image, characteristic information of the original image, and a target detail intensity, generate AI data including the target resolution of the first image, bit depth information of the first image, the AI-upscaling neural network set identification information, and encoding control information, and generate AI encoding data including the image data and the AI data; and a communication interface configured to transmit the AI encoding data to an AI decoding apparatus, wherein the AI data includes information about an AI-upscaling neural network corresponding to the AI-downscaling neural network.

    ELECTRONIC APPARATUS, CONTROL METHOD THEREOF AND ELECTRONIC SYSTEM

    公开(公告)号:US20220084167A1

    公开(公告)日:2022-03-17

    申请号:US17464119

    申请日:2021-09-01

    Abstract: An electronic apparatus is dislcosed. The electronic apparatus includes: a memory configured to store a downscaling network of a first artificial intelligene model, a communication interface comprising communication circuitry, and a processor connected to the memory and the communication interface and configured to control the electronic apparatus, wherein the processor is configured to: obtain an output image in which an input image is downscaled by inputting the input image the downscaling network, control the communication interface to trasnmit the output image to another electronic apparatus, and wherein the first artificial intelligene model is configured to be learned based on: a sample image, a first intermediate image obtained by inputting the sample image to the downscaling network, a first final image obtained by inputting the first intermediate image to an upscaling network of the first artificial intelligene model, a second intermediate image in which the sample image is downscaled by a legacy scaler, and a second final image in which the first intermediate image is upscaled by the legacy scaler.

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