CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12800 > Article
Paper
11 October 2023 Research and application of residual local blueprint separable network for lightweight image super-resolution
Wenjiao Zhang, Guoqiang Wu, Haohui Sun, Wushen Li, Yang Ran
Author Affiliations +
Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280022 (2023) https://doi.org/10.1117/12.3004142
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China
Abstract
Deep learning based Single image super-resolution has achieved great success, but the computational cost is too high, making it unsuitable for real-time tasks on resource-constrained devices. In this paper, we propose Residual Local Blueprint Separable Network (RLBSN), which based on RLFN lightweight backbone network. The blueprint separable convolution was used to replace the traditional convolution, which can enhance the extraction of edge information, reduce the number of model parameters, and improve the running speed. The knowledge distillation concept is introduced to calculate loss function and the output of high-performance model is taken as ground-truth to improve the performance of the model. We design the joint loss function that combines the characteristics of various loss functions to generate high-quality super-resolution images. Inference time can be significantly accelerated by transferring post processing to the GPU.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Wenjiao Zhang, Guoqiang Wu, Haohui Sun, Wushen Li, and Yang Ran "Research and application of residual local blueprint separable network for lightweight image super-resolution", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280022 (11 October 2023); https://doi.org/10.1117/12.3004142
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 7 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Convolution
Data modeling
Image processing
Super resolution
Feature extraction
Performance modeling
Education and training
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top