公开(公告)号：US11593916B2

公开(公告)日：2023-02-28

申请号：US17029554

申请日：2020-09-23

Applicant: Huawei Technologies Co., Ltd.

Inventor： Chunfeng Yao ,  Bailan Feng ,  Bo Yan ,  Ke Li ,  Bahetiyaer Bare ,  Li Qian

IPC: G06T3/40 ,  G06V10/48 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82

Abstract: An image super-resolution method includes preprocessing the low-resolution image to obtain a vertical gradient map, a horizontal gradient map, and a luminance map, which are used as three different dimensions of information to constitute a to-be-input feature map, performing size conversion on the to-be-input feature map to obtain an input feature map, performing nonlinear transformation on the input feature map to obtain an input feature map obtained after the nonlinear transformation, and performing weighted processing on the input feature map and the input feature map obtained after the nonlinear transformation, to obtain an output feature map, performing size conversion on the output feature map to obtain a residual map, and combining the low-resolution image and the residual map to obtain a high-resolution image.

公开(公告)号：US20210004935A1

公开(公告)日：2021-01-07

申请号：US17029554

申请日：2020-09-23

Applicant: Huawei Technologies Co., Ltd.

Inventor： Chunfeng Yao ,  Bailan Feng ,  Bo Yan ,  Ke Li ,  Bahetiyaer Bare ,  Li Qian

IPC: G06T3/40 ,  G06K9/46

Abstract: An image super-resolution method includes preprocessing the low-resolution image to obtain a vertical gradient map, a horizontal gradient map, and a luminance map, which are used as three different dimensions of information to constitute a to-be-input feature map, performing size conversion on the to-be-input feature map to obtain an input feature map, performing nonlinear transformation on the input feature map to obtain an input feature map obtained after the nonlinear transformation, and performing weighted processing on the input feature map and the input feature map obtained after the nonlinear transformation, to obtain an output feature map, performing size conversion on the output feature map to obtain a residual map, and combining the low-resolution image and the residual map to obtain a high-resolution image.