Enhance Low Visibility Image Using Haze-Removal Framework
Author:
Affiliation:
1. Department of Artificial Intelligence and Computer Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10271284.pdf?arnumber=10271284
Reference54 articles.
1. Haze removal using radial basis function networks for visibility restoration applications;chen;IEEE Trans Neural Netw Learn Syst,2018
2. Joint Contrast Enhancement and Exposure Fusion for Real-World Image Dehazing
3. The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations
4. Image Quality Assessment: From Error Visibility to Structural Similarity
5. HazeRD: An outdoor scene dataset and benchmark for single image dehazing
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1. Enhance Dehazed Images Rapidly Without Losing Restoration Accuracy;IEEE Access;2024
2. Coefficient Optimization of Dehazing Algorithm Based on Contrastive Learning;2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science (BCD);2023-12-14
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