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EANet: Depth Estimation Based on EPI of Light Field.

Authors :
Du, Yunzhang
Zhang, Qian
Hua, Dingkang
Hou, Jiaqi
Wang, Bin
Zhu, Sulei
Zhang, Yan
Fang, Yun
Source :
BioMed Research International; 12/28/2021, p1-10, 10p
Publication Year :
2021

Abstract

The light field is an important way to record the spatial information of the target scene. The purpose of this paper is to obtain depth information through the processing of light field information and provide a basis for intelligent medical treatment. In this paper, we first design an attention module to extract the features of light field images and connect all the features as a feature map to generate an attention image. Then, the attention map is integrated with the convolution layer in the neural network in the form of weights to enhance the weight of the subaperture viewpoint, which is more meaningful for depth estimation. Finally, the obtained initial depth results were optimized. The experimental results show that the MSE, PSNR, and SSIM of the depth map obtained by this method are increased by about 13%, 10 dB, and 4%, respectively, in some scenarios with good performance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23146133
Database :
Complementary Index
Journal :
BioMed Research International
Publication Type :
Academic Journal
Accession number :
154359439
Full Text :
https://doi.org/10.1155/2021/8293151