Dehazing using multiscale(processing) dark channel prior
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Updated
Aug 6, 2024 - Python
Dehazing using multiscale(processing) dark channel prior
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
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.
Image dehazing by convolutional neural network
Single Image Haze Removal Using Dark Channel Prior
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"
Implementation of Dark Channel Fog Removal Algorithms with MATLAB
A python package of robust and effective defogging/dehazing method
Dataset and code of our AAAI2022 paper "Transmission-Guided Bayesian Generative Model for Smoke Segmentation"
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