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公开(公告)号：US20210065337A1
公开(公告)日：2021-03-04
申请号：US16708300
申请日：2019-12-09
Applicant: Novatek Microelectronics Corp.
Inventor： Yu Bai
Abstract: The disclosure provides methods and image processing devices for image super resolution, image enhancement, and convolutional neural network (CNN) model training. The method for image super resolution includes the following steps. An original image is received, and a feature map is extracted from the original image. The original image is segmented into original patches. Each of the original patches is classified respectively into one of patch clusters according to the feature map. The original patches are processed respectively by different pre-trained CNN models according to the belonging patch clusters to obtain predicted patches. A predicted image is generated based on the predicted patches.
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公开(公告)号：US10225607B1
公开(公告)日：2019-03-05
申请号：US15889226
申请日：2018-02-06
Applicant: Novatek Microelectronics Corp.
Inventor： Yu Bai , YuanJia Du , JianHua Liang , Xin Huang , Cong Zhang , Kai Kang
IPC: G06N3/04 , H04N19/80 , H04N21/25 , H04N21/236 , H04N21/434 , H04N21/466 , H04N21/2343 , H04N21/4402
Abstract: The disclosure is directed to a video processing apparatus and a video processing method thereof. In one of the exemplary embodiments, the disclosure is directed to a video processing apparatus which includes not limited to a storage medium configured to store a first video file, a down-scaling module coupled to the storage medium and configured to down-scale the first video file into a second video file, a learning machine module configured to receive the first video file and a third video file which is processed from the second multimedia file and generate a trained model out of the first video file and the third video file, and a transmitter configured to transmit a data package which comprises a compression of the second video file and a compression of the trained model.
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公开(公告)号：US11301965B2
公开(公告)日：2022-04-12
申请号：US16708300
申请日：2019-12-09
Applicant: Novatek Microelectronics Corp.
Inventor： Yu Bai
Abstract: The disclosure provides methods and image processing devices for image super resolution, image enhancement, and convolutional neural network (CNN) model training. The method for image super resolution includes the following steps. An original image is received, and a feature map is extracted from the original image. The original image is segmented into original patches. Each of the original patches is classified respectively into one of patch clusters according to the feature map. The original patches are processed respectively by different pre-trained CNN models according to the belonging patch clusters to obtain predicted patches. A predicted image is generated based on the predicted patches.
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