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公开(公告)号：US08792737B2
公开(公告)日：2014-07-29
申请号：US13969841
申请日：2013-08-19
Applicant: Samsung Electronics Co., Ltd.
Inventor： Tammy Lee , Woo-jin Han , Jianle Chen , Hae-kyung Jung
CPC classification number: H04N19/625 , G06T9/00 , H04N19/107 , H04N19/119 , H04N19/122 , H04N19/169 , H04N19/176 , H04N19/61 , H04N19/70 , H04N19/96
Abstract: Disclosed are an image encoding method and apparatus for encoding an image by grouping a plurality of adjacent prediction units into a transformation unit and transforming the plurality of adjacent prediction into a frequency domain, and an image decoding method and apparatus for decoding an image encoded by using the image encoding method and apparatus.
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62.发明授权Method and apparatus for encoding and decoding image by using large transformation unit 有权通过使用大变换单元对图像进行编码和解码的方法和装置公开(公告)号：US08515190B2
公开(公告)日：2013-08-20
申请号：US13670149
申请日：2012-11-06
Applicant: Samsung Electronics Co., Ltd.
Inventor： Tammy Lee , Woo-jin Han , Jianle Chen , Hae-kyung Jung
CPC classification number: H04N19/625 , G06T9/00 , H04N19/107 , H04N19/119 , H04N19/122 , H04N19/169 , H04N19/176 , H04N19/61 , H04N19/70 , H04N19/96
Abstract: Disclosed are an image encoding method and apparatus for encoding an image by grouping a plurality of adjacent prediction units into a transformation unit and transforming the plurality of adjacent prediction into a frequency domain, and an image decoding method and apparatus for decoding an image encoded by using the image encoding method and apparatus.
Abstract translation: 公开了一种图像编码方法和装置，用于通过将多个相邻预测单元分组为变换单元并将多个相邻预测变换为频域来对图像进行编码，以及图像解码方法和装置，用于对通过使用 图像编码方法和装置。
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公开(公告)号：US12020621B2
公开(公告)日：2024-06-25
申请号：US17710074
申请日：2022-03-31
Applicant: Samsung Electronics Co., Ltd.
Inventor： Kwangdon Kim , Jaesung Lee , Tammy Lee
IPC: G09G3/20
CPC classification number: G09G3/2003 , G09G2320/0626 , G09G2320/0666
Abstract: A method of controlling an element of a display device is provided. At least one processor of the display device may be configured to determine a first chromaticity value corresponding to a first grayscale value of the element of the display device, and determine a first luminance value corresponding to the first chromaticity value, based on the first chromaticity value and a target with respect to a relationship between chromaticity and luminance. In addition, the at least one processor of the display device may be configured to determine a second grayscale value corresponding to the first luminance value, determine a second chromaticity value corresponding to the second grayscale value, determine a second luminance value corresponding to the second chromaticity value, based on the second chromaticity value and the target, and determine chromaticity and luminance calibration coefficients, based on the second luminance value.
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64.发明授权公开(公告)号：US11921822B2
公开(公告)日：2024-03-05
申请号：US17299607
申请日：2019-10-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaeyeon Park , Iljun Ahn , Yongsup Park , Jaehee Kwak , Tammy Lee , Minsu Cheon
CPC classification number: G06F18/22 , G06N3/04 , G06T7/11 , G06V10/40 , G06V10/759
Abstract: Provided are an image processing apparatus and an operation method of the image processing apparatus. The image processing apparatus includes a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory to, by using one or more convolution neural networks, extract target features by performing a convolution operation between features of target regions having same locations in a plurality of input images and a first kernel set, extract peripheral features by performing a convolution operation of features of peripheral regions located around the target regions in the plurality of input images and a second kernel set, and determine a feature of a region corresponding to the target regions in an output image, based on the target features and the peripheral features.
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65.发明授权公开(公告)号：US11917191B2
公开(公告)日：2024-02-27
申请号：US18105594
申请日：2023-02-03
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Tammy Lee , Jianle Chen
IPC: H04N19/52 , H04N19/513 , H04N19/517 , H04N19/105 , H04N19/139 , H04N19/65 , H04N19/176
CPC classification number: H04N19/52 , H04N19/105 , H04N19/139 , H04N19/513 , H04N19/517 , H04N19/521 , H04N19/65 , H04N19/176
Abstract: Provided are methods and apparatus for encoding and decoding motion information. The method of encoding motion information includes: obtaining a motion information candidate by using motion information of prediction units that are temporally or spatially related to a current prediction unit; adding, when the number of motion information included in the motion information candidate is smaller than a predetermined number n, alternative motion information to the motion information candidate so that the number of motion information included in the motion information candidate reaches the predetermined number n; determining motion information with respect to the current prediction unit from among the n motion information candidates; and encoding index information indicating the determined motion information as motion information of the current prediction unit.
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Patent Agency Ranking
公开(公告)号：US11871144B2
公开(公告)日：2024-01-09
申请号：US17256560
申请日：2019-07-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Iljun Ahn , Yongsup Park , Jaeyeon Park , Tammy Lee , Minsu Cheon
CPC classification number: H04N7/0117 , G06F18/22 , G06N3/045 , G06N3/08 , G06T3/4007 , G06T3/4046 , G06T5/002 , G06T2207/10016 , G06T2207/20084 , G06T2207/20182
Abstract: Provided is an image processing apparatus for generating a high-resolution image. The image processing apparatus 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 extract feature information regarding a low-resolution image of a current frame by using a first convolutional neural network, generate, based on the feature information, a first high-resolution image of the current frame, remove flickering of the first high-resolution image by using a high-resolution image of a previous frame, and remove flickering of a high-resolution image of a next frame by using at least one of a flickering-removed second high-resolution image of the current frame, or the feature information.
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公开(公告)号：US11861808B2
公开(公告)日：2024-01-02
申请号：US16971625
申请日：2019-02-20
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaeyeon Park , Iljun Ahn , Yongsup Park , Tammy Lee , Minsu Cheon
CPC classification number: G06T3/4053 , G06F17/18 , G06N3/08 , G06T3/4007 , G06T5/20
Abstract: An electronic device is disclosed. The electronic device of the disclosure comprises: a memory in which a learned artificial intelligence model is stored; and a processor for inputting an input image to the artificial intelligence model and outputting an enlarged image with increased resolution, wherein the learned artificial intelligence model includes an upscaling module for acquiring the pixel values of interpolated pixels around a cell according to a function having a nonlinearly decreasing symmetric form with reference to an original pixel in the enlarged image, the original pixel corresponding to a pixel of the input image.
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公开(公告)号：US11836890B2
公开(公告)日：2023-12-05
申请号：US17527732
申请日：2021-11-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Cheon Lee , Donghyun Kim , Yongsup Park , Jaeyeon Park , Iljun Ahn , Hyunseung Lee , Taegyoung Ahn , Youngsu Moon , Tammy Lee
CPC classification number: G06T3/403 , G06T3/4053 , G06T7/13 , G06V10/82 , G06T2207/20081
Abstract: An image processing apparatus applies an image to a first learning network model to optimize the edges of the image, applies the image to a second learning network model to optimize the texture of the image, and applies a first weight to the first image and a second weight to the second image based on information on the edge areas and the texture areas of the image to acquire an output image.
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公开(公告)号：US20230360382A1
公开(公告)日：2023-11-09
申请号：US18136614
申请日：2023-04-19
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Soomin KANG , Youngchan Song , Tammy Lee , Jaeyeon Park , Hanul Shin , Iljun Ahn
IPC: G06V10/82 , G06V10/77 , G06V10/774 , G06T5/00 , G06T5/50 , G06F16/532
CPC classification number: G06V10/82 , G06V10/7715 , G06V10/774 , G06T5/002 , G06T5/50 , G06F16/532 , G06T2207/20192 , G06T2207/20021 , G06T2207/20084 , G06T2207/20081
Abstract: An image processing apparatus for processing an image by using one neural network, includes: a memory storing one instruction; and one processor configured to execute the one instruction to: obtain first feature data, based on a first image, obtain pieces of second feature data corresponding to first areas of the first image by performing first image processing on the first feature data, the first areas comprising a first number of pixels, obtain third feature data, based on the first image, obtain pieces of fourth feature data corresponding to second areas of the first image, by performing second image processing on the third feature data, the second areas comprising a second number of pixels that is greater than the first number, and generate a second image, based on the pieces of second feature data and the pieces of fourth feature data.
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70.发明授权公开(公告)号：US11379955B2
公开(公告)日：2022-07-05
申请号：US16971601
申请日：2019-02-20
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Tejas Nair , Jaesung Lee , Tammy Lee
Abstract: The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm, including deep learning and the like, and application thereof. In particular, an electronic device of the present disclosure comprises: a memory including at least one command; and a processor connected to the memory so as to control the electronic device, wherein, by executing the at least one command, the processor acquires an image, acquires a noise correction map for correction of noise of the image on the basis of configuration information of a camera having captured the image or brightness information of the image, and eliminates the noise of the image through the noise correction map. In particular, at least a part of an image processing method may use an artificial intelligence model having been acquired through learning according to at least one of a machine learning algorithm, a neural network algorithm, and a deep learning algorithm.
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