US 12,293,436 B2
Image reconstruction method, device, equipment, system and computer-readable storage medium
Ran Cheng, Suzhou (CN); and Qingguo Xie, Suzhou (CN)
Assigned to RAYCAN TECHNOLOGY CO., LTD. (SUZHOU), (CN)
Appl. No. 17/791,093
Filed by RAYCAN TECHNOLOGY CO., LTD. (SUZHOU), Suzhou (CN)
PCT Filed Nov. 27, 2020, PCT No. PCT/CN2020/132370
§ 371(c)(1), (2) Date Jul. 6, 2022,
PCT Pub. No. WO2021/139439, PCT Pub. Date Jul. 15, 2021.
Claims priority of application No. 202010012326.1 (CN), filed on Jan. 7, 2020.
Prior Publication US 2023/0036359 A1, Feb. 2, 2023
Int. Cl. G06T 11/00 (2006.01); G06N 3/04 (2023.01); G06T 3/4007 (2024.01); G06V 10/44 (2022.01)
CPC G06T 11/003 (2013.01) [G06N 3/04 (2013.01); G06T 3/4007 (2013.01); G06V 10/44 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An image reconstruction method based on a target reconstruction model, wherein the target reconstruction model comprises a first convolutional layer, a residual network module, a densely connected network module and a second convolutional layer, and the image reconstruction method comprises:
invoking the first convolutional layer to extract shallow layer features from an obtained image to be reconstructed;
invoking the residual network module to obtain middle layer features from the shallow layer features;
invoking the densely connected network module to obtain deep layer features from the middle layer features; and
invoking the second convolutional layer to perform image reconstruction on the deep layer features so as to obtain a reconstructed image of the image to be reconstructed.