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公开(公告)号：US10937197B2
公开(公告)日：2021-03-02
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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公开(公告)号：US10825206B2
公开(公告)日：2020-11-03
申请号：US16821609
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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公开(公告)号：US10825203B2
公开(公告)日：2020-11-03
申请号：US16570057
申请日：2019-09-13
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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公开(公告)号：US10825140B1
公开(公告)日：2020-11-03
申请号：US16826851
申请日：2020-03-23
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Heechul Yang , Jongseok Lee , Youngo Park , Kwangpyo Choi
Abstract: Provided are methods and apparatus related to Artificial Intelligence (AI) downscaling and upscaling and techniques related to reducing artifact problems. Some embodiments include down-scaling an original image through a Deep Neural Network (DNN); generating, from the original image and based on frequency transform coefficients, artifact information representing a region in the first image including an artifact in the first image. Post-processing may be performed based on the artifact information to change pixels in the first image, thus reducing the effect of artifacts.
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公开(公告)号：US10817990B1
公开(公告)日：2020-10-27
申请号：US16850411
申请日：2020-04-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Heechul Yang , Jongseok Lee , Youngo Park , Kwangpyo Choi
Abstract: Provided are methods and apparatus related to Artificial Intelligence (AI) downscaling and upscaling and techniques related to reducing artifact problems. Some embodiments include down-scaling an original image through a Deep Neural Network (DNN); generating, from the original image and based on frequency transform coefficients, artifact information representing a region in the first image including an artifact in the first image. Post-processing may be performed based on the artifact information to change pixels in the first image, thus reducing the effect of artifacts.
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Patent Agency Ranking
公开(公告)号：US10817988B2
公开(公告)日：2020-10-27
申请号：US16824486
申请日：2020-03-19
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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公开(公告)号：US10817987B2
公开(公告)日：2020-10-27
申请号：US16822665
申请日：2020-03-18
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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公开(公告)号：US12262039B2
公开(公告)日：2025-03-25
申请号：US17713693
申请日：2022-04-05
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Woongil Choi , Minwoo Park , Kwangpyo Choi , Kiho Choi
IPC: H04N19/176 , H04N19/184 , H04N19/189 , H04N19/46
Abstract: An image decoding method may include: receiving a bitstream generated as a result of encoding an image sequence; obtaining, from a sequence parameter set of the bitstream, a first tool set index indicating a tool allowed to decode the bitstream among a plurality of tools; obtaining, from the sequence parameter set, tool flags based on the tool flags, identifying a tool that has been used to encode the image sequence among the plurality of tools; and reconstructing the image sequence based on the identified tool, wherein values of the tool flags are set according to a value of the first tool set index.
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公开(公告)号：US12229921B2
公开(公告)日：2025-02-18
申请号：US17554827
申请日：2021-12-17
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh Dinh , Kyonghwan Jin , Kwangpyo Choi
Abstract: An image processing apparatus, including a memory configured to store one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to cause the image processing apparatus to: identify, in a previous frame, a prediction sample corresponding to a current sample of a current frame, generate a prediction frame for the current frame by changing a sample value of a collocated sample of the previous frame according to a sample value of the prediction sample, derive a weight by comparing a sample value of the current sample with the sample value of the prediction sample, apply the weight to a collocated sample of the prediction frame to obtain a weighted prediction frame, and obtain a current output frame by processing the current frame and the weighted prediction frame through a neural network comprising a convolution layer.
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60.发明授权公开(公告)号：US12096131B2
公开(公告)日：2024-09-17
申请号：US17512338
申请日：2021-10-27
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Quockhanh Dinh , Kyonghwan Jin , Youngo Park , Kwangpyo Choi
IPC: G06T7/90 , G06F18/214 , G06F18/40 , G06N20/00 , G06T3/4015 , G06T3/4038 , G06T5/20 , G06T5/70 , H04N23/81 , H04N23/90
CPC classification number: H04N23/81 , G06F18/2148 , G06F18/40 , G06N20/00 , G06T3/4015 , G06T3/4038 , G06T5/20 , G06T5/70 , G06T7/90 , H04N23/90 , G06T2207/10016 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/20182
Abstract: A method includes obtaining, by a second processor of the electronic device, from a first processor of the electronic device, a control signal for obtaining image data, loading any one learning model of at least one learning model into a memory, obtaining, by using the camera module, raw image data of the object, from light reflected from the object, the raw image data being configured to have a specified color array consisting of a plurality of colors with respect to a plurality of pixels, obtaining, by using the loaded any one learning model, a color data set with respect to the plurality of pixels from the obtained raw image data, the color data set including a plurality of pieces of color data classified according to the plurality of colors, and obtaining the noise-reduced image data of the object by using the obtained color data set.
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