Dehazing using multiscale(processing) dark channel prior
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Updated
Aug 6, 2024 - Python
Dehazing using multiscale(processing) dark channel prior
Real Scene Single Image Dehazing Network with Multi-Prior Guidance and Domain Transfer [IEEE TMM 2025]
[NC2021] Prior guided conditional generative adversarial network for single image dehazing
深圳大学金融科技学院2024-2025第一学期人工智能与机器学习课程第六组期末作业
[Pattern Recognition 2023] Physical Model and Image Translation Fused Network for Single-Image Dehazing
This repo is based on an Autoencoder model for image dehazing from different types of hazes like smog, smoke or fog or even in fire inicidents
Image dehazing by convolutional neural network
Single Image Haze Removal Using Dark Channel Prior
In this Project, important algorithms such as Canny Edge Detection, Harris Corner Detection, Segmentation, and Dehazing are utilized. These algorithms perform operations like detecting edges and corners in images, segmenting different regions, and enhancing foggy or blurred images.
实现了图片处理功能的平台,完成了数据库的持久化存储
Lightweight and Efficient Image Dehazing Network Guided by Transmission Estimation from Real-world Hazy Scenes; accepted by Sensors 2021, 21(3), 960, MDPI; https://doi.org/10.3390/s21030960
This is an python implementation of "single image haze removal using dark channel prior"
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