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公开(公告)号：US20230044603A1
公开(公告)日：2023-02-09
申请号：US17880840
申请日：2022-08-04
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Yinji PIAO , Kyungah KIM , Quockhanh DINH , Minsoo PARK
IPC: H04N19/132 , H04N19/30 , H04N19/105 , H04N19/176
Abstract: Provided is an image processing apparatus including a memory storing instructions, and a processor configured to operate based on the instructions to reconstruct a current block from encoded data of the current block, obtain a quantization error map including sample values calculated based on a quantization parameter included in the encoded data, obtain a first modified block by applying the current block and the quantization error map to a neural network, obtain a first differential block between the current block and the first modified block, obtain a second differential block by changing sample values of the first differential block based on a parameter dependent on a feature of the current block, and obtain a second modified block by combining the current block and the second differential block.
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公开(公告)号：US20220272352A1
公开(公告)日：2022-08-25
申请号：US17677414
申请日：2022-02-22
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh DINH , Kwangpyo CHOI
IPC: H04N19/137 , H04N19/43 , H04N19/91 , H04N19/124 , H04N19/51
Abstract: An image decoding method using artificial intelligence (AI), including obtaining feature data of a current optical flow and feature data of current differential data from a bitstream corresponding to a current image; obtaining the current optical flow by applying the feature data of the current optical flow to a neural-network-based first decoder; applying at least one of the feature data of the current optical flow and feature data of a previous optical flow to a first preprocessing neural network; obtain a first concatenation result by concatenating feature data obtained from the first preprocessing neural network with the feature data of the current differential data; obtaining the current differential data by applying the first concatenation result to a neural-network-based second decoder; and reconstructing the current image using the current differential data and a current predicted image generated from a previous reconstructed image based on the current optical flow.
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13.发明申请公开(公告)号：US20200184685A1
公开(公告)日：2020-06-11
申请号：US16793605
申请日：2020-02-18
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehwan KIM , Jongseok LEE , Sunyoung JEON , Kwangpyo CHOI , Minseok CHOI , Quockhanh DINH , Youngo PARK
Abstract: Provided is an artificial intelligence (AI) decoding apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, the processor is configured to: obtain AI data related to AI down-scaling an original image to a first image; obtain image data corresponding to an encoding result on the first image; obtain a second image corresponding to the first image by performing a decoding on the image data; obtain deep neural network (DNN) setting information among a plurality of DNN setting information from the AI data; and obtain, by an up-scaling DNN, a third image by performing the AI up-scaling on the second image, the up-scaling DNN being configured with the obtained DNN setting information, wherein the plurality of DNN setting information comprises a parameter used in the up-scaling DNN, the parameter being obtained through joint training of the up-scaling DNN and a down-scaling DNN, and wherein the down-scaling DNN is used to obtain the first image from the original image.
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14.发明公开公开(公告)号：US20240129546A1
公开(公告)日：2024-04-18
申请号：US18372409
申请日：2023-09-25
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh DINH , Kyungah KIM , Minsoo PARK , Minwoo PARK , Kwangpyo CHOI , Yinji PIAO
IPC: H04N19/85 , H04N19/176
CPC classification number: H04N19/85 , H04N19/176
Abstract: An artificial intelligence (AI)-based image decoding method and an apparatus performing the AI-based image decoding method are provided. According to the AI-based image decoding method, a transform block for a residual block of a current block is obtained from a bitstream, a transform kernel for the transform block is generated by applying, to a neural network, a prediction block for the current block, neighboring pixels of the current block, and coding context information, the residual block is obtained by applying the generated transform kernel to the transform block, and the current block is reconstructed by using the residual block and the prediction block.
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公开(公告)号：US20240073425A1
公开(公告)日：2024-02-29
申请号：US18237150
申请日：2023-08-23
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh DINH , Hyungmin ROH , Minwoo PARK , Kwangpyo CHOI
IPC: H04N19/139 , H04N19/172 , H04N19/42 , H04N19/52
CPC classification number: H04N19/139 , H04N19/172 , H04N19/42 , H04N19/52
Abstract: An image encoding method based on artificial intelligence (AI) includes obtaining motion vector feature data of a current frame by inputting the current frame and a reference frame to a motion vector encoder and applying a plurality of resolution scales to the current frame and the reference frame via the motion vector encoder; obtaining a current motion vector by inputting the motion vector feature data to a motion vector decoder; obtaining a current predicted image based on the current motion vector and the reference frame; and generating a bitstream based on the motion vector feature data and the current predicted image.
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Patent Agency Ranking
公开(公告)号：US20210142445A1
公开(公告)日：2021-05-13
申请号：US17091889
申请日：2020-11-06
Applicant: SAMSUNG ELECTRONICS CO,. LTD.
Inventor： Quockhanh DINH , Kwangpyo CHOI , Yongsup PARK , Jaeyeon PARK
Abstract: An artificial intelligence (AI) decoding apparatus obtains image data corresponding to a first image, which is AI-downscaled from an original image by an AI encoding apparatus by using a first deep neural network (DNN); reconstructs a second image corresponding to the first image, based on the image data; and obtain a third image, which is AI-upscaled from the second image, convolution is performed based on the second image and second parameters of a filter kernel included in a second DNN, wherein each of the second parameters is an integer value, and the second parameters are determined as values associated with first parameters of a filter kernel included in the first DNN. Embodiments use memory-efficient values with respect to filter kernels. Parameters used to obtain the memory-efficient integer values may be obtained via joint training between the first DNN and the second DNN.
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公开(公告)号：US20210134020A1
公开(公告)日：2021-05-06
申请号：US17147954
申请日：2021-01-13
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh DINH , Minseok CHOI , Kwangpyo CHOI
Abstract: Provided is an artificial intelligence (AI) decoding apparatus including a memory storing one or more instructions; and a processor configured to execute the one or more instructions to, when an image is input to a second DNN including a plurality of layers, obtain first result values based on an operation between the image and a first filter kernel and obtain second result values based on an operation between the image and a second filter kernel, from a first layer including the first and second filter kernels from among the plurality of layers, perform normalization by transforming the first result values into first values by using a first scale factor, and, perform normalization by transforming the second result values into second values by using a second scale factor, transform the first values and the second values into integer values included in a preset range.
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18.发明申请公开(公告)号：US20200226717A1
公开(公告)日：2020-07-16
申请号：US16831521
申请日：2020-03-26
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehwan KIM , Jongseok LEE , Sunyoung JEON , Kwangpyo CHOI , Minseok CHOI , Quockhanh DINH , Youngo PARK
Abstract: An artificial intelligence (AI) decoding apparatus includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions, to obtain image data corresponding to a first image that is encoded, obtain a second image corresponding to the first image by decoding the obtained image data, determine whether to perform AI up-scaling of the obtained second image, based on the AI up-scaling of the obtained second image being determined to be performed, obtain a third image by performing the AI up-scaling of the obtained second image through an up-scaling deep neural network (DNN), and output the obtained third image, and based on the AI up-scaling of the obtained second image being determined to be not performed, output the obtained second image.
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19.发明申请公开(公告)号：US20200219293A1
公开(公告)日：2020-07-09
申请号：US16821686
申请日：2020-03-17
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehwan KIM , Jongseok LEE , Sunyoung JEON , Kwangpyo CHOI , Minseok CHOI , Quockhanh DINH , Youngo PARK
Abstract: Provided is an artificial intelligence (AI) decoding apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, the processor is configured to: obtain AI data related to AI down-scaling an original image to a first image; obtain image data corresponding to an encoding result on the first image; obtain a second image corresponding to the first image by performing a decoding on the image data; obtain deep neural network (DNN) setting information among a plurality of DNN setting information from the AI data; and obtain, by an up-scaling DNN, a third image by performing the AI up-scaling on the second image, the up-scaling DNN being configured with the obtained DNN setting information, wherein the plurality of DNN setting information comprises a parameter used in the up-scaling DNN, the parameter being obtained through joint training of the up-scaling DNN and a down-scaling DNN, and wherein the down-scaling DNN is used to obtain the first image from the original image.
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20.发明申请公开(公告)号：US20200151914A1
公开(公告)日：2020-05-14
申请号：US16743618
申请日：2020-01-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh DINH , Minseok CHOI , Kwangpyo CHOI
Abstract: Provided is an artificial intelligence (AI) decoding apparatus including a memory storing one or more instructions; and a processor configured to execute the one or more instructions to, when an image is input to a second DNN including a plurality of layers, obtain first result values based on an operation between the image and a first filter kernel and obtain second result values based on an operation between the image and a second filter kernel, from a first layer including the first and second filter kernels from among the plurality of layers, perform normalization by transforming the first result values into first values by using a first scale factor, and, perform normalization by transforming the second result values into second values by using a second scale factor, transform the first values and the second values into integer values included in a preset range.
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