- Patent Title: Adaptive deformable kernel prediction network for image de-noising
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Application No.: US17090170Application Date: 2020-11-05
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Publication No.: US11869171B2Publication Date: 2024-01-09
- Inventor: Anbang Yao , Ming Lu , Yikai Wang , Xiaoming Chen , Junjie Huang , Tao Lv , Yuanke Luo , Yi Yang , Feng Chen , Zhiming Wang , Zhiqiao Zheng , Shandong Wang
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: INTEL CORPORATION
- Current Assignee: INTEL CORPORATION
- Current Assignee Address: US CA Santa Clara
- Agency: JAFFERY WATSON MENDONSA & HAMILTON LLP
- Priority: CN 1911081492.0 2019.11.07
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06N3/04

Abstract:
Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.
Public/Granted literature
- US20210142448A1 ADAPTIVE DEFORMABLE KERNEL PREDICTION NETWORK FOR IMAGE DE-NOISING Public/Granted day:2021-05-13
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