Underwater Image Enhancement With Hyper-Laplacian Reflectance Priors
Author:
Affiliation:
1. Department of Automation, Tsinghua University, Beijing, China
2. Qualcomm, San Diego, CA, USA
3. School of Computer Science and Engineering, Nanyang Technological University (NTU), Jurong West, Singapore
Funder
Ministry of Science and Technology of the People’s Republic of China
National Natural Science Foundation of China
Postdoctoral Science Foundation of China
National Key Research and Development Program of China
MindSpore, Compute Architecture for Neural Network (CANN), and Ascend AI Processor
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/9626658/09854113.pdf?arnumber=9854113
Reference49 articles.
1. Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior
2. Properties and performance of a center/surround retinex
3. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
4. A Probabilistic Method for Image Enhancement With Simultaneous Illumination and Reflectance Estimation
5. Contrast Enhancement Based on Intrinsic Image Decomposition
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