There are 4 repositories under haze-removal topic.
Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc.
[ACMMM2023] "Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution", https://arxiv.org/abs/2308.01738
[CVPR 2022] Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model
python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
This paper is accepted by ICCV 2021.
[CVPR 2009] Single Image Haze Removal Using Dark Channel Prior
A Python2 implementation of single image haze removal
This is the source code of PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal which has been accepted by IEEE Transaction on Image Processing 2020.
This is the project page of our paper which has been published in ECCV 2020.
Conditional Wasserstein Generative Adversarial Network for image-to-image translation.
This is the source code of PMS-Net: Robust Haze Removal Based on Patch Map for Single Images which has been published in CVPR 2019 Long Beach
A Matlab implementation of haze removal from a single image (RGB and Grayscale)
The Dark Channel Prior technique is implemented on an FPGA using only Verilog code and no Intellectual Property, making it convenient to replicate using any simulator and any of the available FPGA boards, including those from Xilinx and Altera.
Code of the paper "Learning a Patch Quality Comparator for Single Image Dehazing"
The code for haze removal using dark channel prior, which was a part of the self-driving car project
An implementation of "Single Image Haze Removal Using Dark Channel Prior" by He et al. 2009
[INFOCOM 2019] ImgSensingNet: UAV Vision Guided Aerial-Ground Air Quality Sensing System
This is the MATLAB source code of a haze removal algorithm published in Remote Sensing (MDPI) under the title "Robust Single-Image Haze Removal Using Optimal Transmission Map and Adaptive Atmospheric Light". The transmission map was estimated by maximizing an objective function quantifying image contrast and sharpness. Additionally, an adaptive atmospheric light was devised to prevent the loss of dark details after removing haze.
This is an python implementation of "single image haze removal using dark channel prior"
This is the implementation of the dehazing algorithm proposed in IBA-ICICT conference 2019
An Improved Air-Light Estimation Scheme for Single Haze Images Using Color Constancy Prior.
An underwater image enhancement method and a corresponding image super-resolution algorithm. Image enhancement Technique. Super-resolution Convolutional neural networks the Retinex algorithm gamma correction. Dark prior
Haze degrades image quality and limits visibility especially in outdoor settings. This consequently affects performance on other high-level tasks such as object detection and recognition. The AOD network proposed by Boyi Li et. al. is an end-to-end CNN to de-haze an image. AOD takes as input a hazy image and generates a de-hazed image. Here i have implement the given paper AOD-net in Tensorflow.
Haze Removal tool using Dark Channel Prior. Based on work by Kaiming He.
This is the MATLAB implementation of the haziness degree evaluator for predicting the haze density from a single image. The relevant work was published in the MDPI Sensors journal under the title "Haziness degree evaluator: a knowledge-driven approach for haze density estimation".
Single Image Haze Removal Using Dark Channel Prior
This is a MATLAB source code of the enhanced equidistribution, which guarantees that the generated random sequence follows the theoretical uniform distribution.
Matlab Implementation of Image Enhancement using Haze Removal Technique
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