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公开(公告)号:US12198310B2
公开(公告)日:2025-01-14
申请号:US17764458
申请日:2021-03-22
Applicant: BOE Technology Group Co., Ltd.
Inventor: Ran Duan , Dan Zhu , Yanhong Wu , Guannan Chen
Abstract: An image processing method and an image processing device are provided. The image processing method includes performing at least one of a scratch repairing step, a dead point repairing step, a denoising step and a color cast correcting step on a to-be-processed video frame. According to the embodiments of the present disclosure, it is able to repair a scratch and a dead point, remove a noise and/or correct color cast for a video frame, thereby to improve a display effect of the video frame.
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公开(公告)号:US20240202983A1
公开(公告)日:2024-06-20
申请号:US17907012
申请日:2021-12-28
Applicant: BOE Technology Group Co., Ltd.
Inventor: Dan Zhu , Guannan Chen , Hanwen Liu
CPC classification number: G06T11/00 , G06T5/20 , G06T7/73 , G06V10/751 , G06V10/7715 , G06V10/776 , G06V10/82 , G06T2207/10016 , G06T2207/20084 , G06T2207/30201 , G06T2210/44
Abstract: A computer-implemented method is provided. The computer-implemented method includes inputting a low-resolution image and a plurality of high-resolution images into a feature extractor, the low-resolution image and the plurality of high-resolution images including images of a target object; obtaining, by the feature extractor, feature maps of the low-resolution image and the plurality of high-resolution images; comparing similarities between the feature maps of the low-resolution image and the plurality of high-resolution images; obtaining selected feature maps of one or more selected high-resolution images of the plurality of high-resolution images most similar to the low-resolution image; inputting the selected feature maps into a generator to output a repair image; enhancing the low-resolution image using a pre-processing image enhancing process to generate an enhanced image; and morphing the repair image with the enhanced image.
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公开(公告)号:US11765305B2
公开(公告)日:2023-09-19
申请号:US16979417
申请日:2019-12-19
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor: Yanhong Wu , Hanwen Liu , Guannan Chen
CPC classification number: H04N1/6022
Abstract: An embodiment of the present disclosure provides a method for processing an image. The method comprise: determining weights corresponding to candidate colors for a target color based on an original color of a pixel in the image; selecting a target color of the pixel from the candidate colors based on the weights; and converting the original color of the pixel into the target color to obtain a target image. According to the embodiment of the present disclosure, by determining the weights of the candidate colors, the image can be converted into the target image comprising only the candidate colors, thereby using a limited number of candidate colors to represent the target image.
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4.
公开(公告)号:US11295115B2
公开(公告)日:2022-04-05
申请号:US16937175
申请日:2020-07-23
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor: Yanhong Wu , Guannan Chen , Lijie Zhang
IPC: G06K9/00
Abstract: The present disclosure discloses a method for generating a face image, an electronic device, and a non-transitory computer-readable storage medium, the method includes: receiving a first face image and target facial expression information, and determining first facial expression information corresponding to the first face image; selecting a first reference face image matched with the first facial expression information and a second reference face image matched with the target facial expression information from a face image library; respectively extracting feature points in the first reference face image and the second reference face image, and determining face deformation information between the first reference face image and the second reference face image based on the feature points; and extracting feature points in the first face image, and generating a second face image based on the face deformation information and the feature points in the first face image.
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公开(公告)号:US11244151B2
公开(公告)日:2022-02-08
申请号:US16639934
申请日:2019-10-10
Applicant: BOE Technology Group Co., Ltd.
Inventor: Guannan Chen , Honghong Jia , Lijie Zhang
Abstract: A computer-implemented method of recognizing a facial expression of a subject in an input image is provided. The method includes filtering the input image to generate a plurality of filter response images; inputting the input image into a first neural network; processing the input image using the first neural network to generate a first prediction value; inputting the plurality of filter response images into a second neural network; processing the plurality of filter response images using the second neural network to generate a second prediction value; weighted averaging the first prediction value and the second prediction value to generate a weighted average prediction value; and generating an image classification result based on the weighted average prediction value.
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公开(公告)号:US12125182B2
公开(公告)日:2024-10-22
申请号:US17754192
申请日:2021-04-27
Applicant: BOE Technology Group Co., Ltd.
Inventor: Guannan Chen , Dan Zhu , Lijie Zhang
CPC classification number: G06T5/90 , G06T7/90 , G06T9/00 , G06V10/44 , G06V10/56 , H04N1/6019 , G06T2207/10024 , G06T2207/20081 , G06T2207/20208
Abstract: The present disclosure provides an image processing method and an image processing apparatus. The image processing method includes: obtaining a to-be-converted SDR image; using a first convolutional network to perform feature analysis on the SDR image, to obtain N weights of the SDR image; where the N weights are respectively configured to characterize proportions of color information of the SDR image to color information characterized in preset N 3D lookup tables, the N 3D lookup tables are configured to characterize color information of different types; obtaining a first 3D lookup table for the SDR image according to the N weights and the N 3D lookup tables; using the first 3D lookup table to adjust the color information of the SDR image to obtain an HDR image; and using a second convolutional neural network to perform refinement correction on the HDR image to obtain an output image.
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公开(公告)号:US12125174B2
公开(公告)日:2024-10-22
申请号:US17626162
申请日:2020-12-24
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor: Guannan Chen , Ran Duan , Mengdi Sun , Lijie Zhang
CPC classification number: G06T5/70 , G06T3/4046 , G06T5/20 , G06T5/50 , G06V10/7715 , G06V40/166 , G06V40/168 , G06T2207/20028 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221
Abstract: An image processing method and device, and a computer-readable storage medium are disclosed. The method includes: performing a channel expansion process on the input image to obtain a first intermediate image; performing a channel decomposition process for multiple times based on the first intermediate image, wherein each time of channel decomposition process includes: decomposing an image to be processed into a first decomposition image and a second decomposition image; concatenating first decomposition images generated in each time of channel decomposition process and second decomposition image generated in the last time of channel decomposition process to obtain a concatenated image; performing a post-processing process on the concatenated image to obtain a second intermediate image; and fusing the second intermediate image with the input image to obtain the first output image.
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8.
公开(公告)号:US20240233313A1
公开(公告)日:2024-07-11
申请号:US17928087
申请日:2021-10-28
Applicant: BOE Technology Group Co., Ltd.
Inventor: Ran Duan , Guannan Chen
CPC classification number: G06V10/44 , G06T5/20 , G06T5/73 , G06T7/11 , G06T7/13 , G06V10/771 , G06V10/806
Abstract: A model training method includes: acquiring a sample set, wherein samples in the sample set include a blurred image and a sharp image of a same fingerprint; inputting the blurred image into a convolutional neural network, performing, by an encoding network in the convolutional neural network, down-sampling and feature extraction to the blurred image, to output a plurality of feature maps, and performing, by a decoding network in the convolutional neural network, up-sampling and feature extraction to the feature maps, to output a predicted image corresponding to the blurred image; according to the predicted image, the sharp image and a predetermined loss function, calculating a loss value of the convolutional neural network, and, with minimizing the loss value as a target, adjusting parameters of the convolutional neural network; and determining the convolutional neural network of which the parameters are adjusted to be an image processing model.
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公开(公告)号:US11915058B2
公开(公告)日:2024-02-27
申请号:US17407145
申请日:2021-08-19
Applicant: BOE Technology Group Co., Ltd.
Inventor: Wenbin Chen , Yan Gao , Guannan Chen
IPC: G06F3/00 , G06F9/48 , G06F9/50 , H04N19/124 , H04N19/176
CPC classification number: G06F9/5066 , G06F9/485 , G06F9/505 , H04N19/124 , H04N19/176
Abstract: A video processing method and device, electronic equipment and a storage medium, which are applied to the technical field of computers. The method comprises: acquiring video data to be processed; generating video enhancement tasks corresponding to each video frame in the video data to be processed, the video enhancement task comprising a plurality of video enhancement subtasks; and simultaneously executing at least two different video enhancement subtasks of the plurality of video frames in a multi-thread concurrent manner, a single thread correspondingly executing one video enhancement subtask.
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公开(公告)号:US20230342892A1
公开(公告)日:2023-10-26
申请号:US17635263
申请日:2021-04-30
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor: Guannan Chen , Mengdi Sun , Yan Gao , Lijie Zhang
CPC classification number: G06T5/007 , G06T5/20 , G06V10/761 , G06T2207/20081 , G06T2207/20208
Abstract: An image processing method, an apparatus, an electronic device and a non-transient computer-readable storage medium. The image processing method includes: (S11) acquiring an original image; (S12) performing a fuzzy processing to the original image to obtain a fuzzy image; (S13) performing a high-dynamic-range image to the original image by using a first network model obtained by pre-training, to obtain a first characteristic matrix, wherein the first network model includes a dense residual module and a gate-control-channel conversion module; (S14) obtaining an auxiliary characteristic matrix of the original image according to the fuzzy image, wherein the auxiliary characteristic matrix includes detail information of the original image and/or low-frequency information of the original image; (S15) obtaining a target image according to the first characteristic matrix and the auxiliary characteristic matrix.
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