/MRP

Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

MRP

Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior, CVPR 2017.

The code has been tested on Win7/10 with Opencv 2.7.

Installation

Please install opencv 2.4.9 (or copy "opencv_core249.dll" "opencv_highgui249.dll " "opencv_imgproc249.dll" from "OPENCV_DIR/build/x64/vc10/bin/" to the same directory with "NighttimeDehaze.exe") before running this code.

Then, run the executable code as: "NighttimeDehazeMRP.exe name.bmp 0", where "name.bmp" is the input nighttime hazy image, the follwowing parameter indicates the algorithm being used, e.g., 0 for MRP and 1 for MRP-Faster, the output dehazed result is named as "name_J.bmp".

Folder Structure

MRP
    -data
        Some test images and the corresponding results generated by this code.
    -NighttimeDehazeMRP.exe
        The executable code
    -*.dll
        The dependencies
    -flickr14.bmp
        A test image

Citation

Please cite our paper in your publications if it helps your research:

@CONFERENCE{CVPR_2017_Jing,
    author = {Jing Zhang and Yang Cao and Shuai Fang and Yu Kang and Chang Wen Chen},
	title = {Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior},
	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2017}
}

Related Work

[1]. Nighttime haze removal based on a new imaging model, ICIP 2014. NighttimeDehaze: Project, NighttimeDehaze: github

[2]. Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images, ACM MM 2018. FPC-Net: Project, FPC-Net: github

[3]. FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing Network, T-IP, 2019. FAMED-Net: Project, FAMED-Net: github

Contact

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