Kaiming早在09年以MSRA实习生的身份获得CVPR best paper，其成果就是给图像去雾。当时并没有用深度学习，却能实现让人震惊的效果。

先看下效果：

左边是原图，右边是去雾霾之后的图。效果还是很惊人的吧。代码也非常简短，如下：

requirements:

opencv3

python3

用法：

python dehaze.py xxx.jpg

import cv2

import math

import numpy as np


def DarkChannel(im,sz):

    b,g,r = cv2.split(im)

    dc = cv2.min(cv2.min(r,g),b);

    kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(sz,sz))

    dark = cv2.erode(dc,kernel)

    return dark


def AtmLight(im,dark):

    [h,w] = im.shape[:2]

    imsz = h*w

    numpx = int(max(math.floor(imsz/1000),1))

    darkvec = dark.reshape(imsz,1);

    imvec = im.reshape(imsz,3);


    indices = darkvec.argsort();

    indices = indices[imsz-numpx::]
    

    atmsum = np.zeros([1,3])

    for ind in range(1,numpx):

    atmsum = atmsum + imvec[indices[ind]]


    A = atmsum / numpx;

    return A


def TransmissionEstimate(im,A,sz):

    omega = 0.95;

    im3 = np.empty(im.shape,im.dtype);


    for ind in range(0,3):

    im3[:,:,ind] = im[:,:,ind]/A[0,ind]


    transmission = 1 - omega*DarkChannel(im3,sz);

    return transmission


def Guidedfilter(im,p,r,eps):

    mean_I = cv2.boxFilter(im,cv2.CV_64F,(r,r));

    mean_p = cv2.boxFilter(p, cv2.CV_64F,(r,r));

    mean_Ip = cv2.boxFilter(im*p,cv2.CV_64F,(r,r));

    cov_Ip = mean_Ip - mean_I*mean_p;


    mean_II = cv2.boxFilter(im*im,cv2.CV_64F,(r,r));

    var_I = mean_II - mean_I*mean_I;


    a = cov_Ip/(var_I + eps);

    b = mean_p - a*mean_I;


    mean_a = cv2.boxFilter(a,cv2.CV_64F,(r,r));

    mean_b = cv2.boxFilter(b,cv2.CV_64F,(r,r));


    q = mean_a*im + mean_b;

    return q;


def TransmissionRefine(im,et):

    gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY);

    gray = np.float64(gray)/255;

    r = 60;

    eps = 0.0001;

    t = Guidedfilter(gray,et,r,eps);


    return t;


def Recover(im,t,A,tx = 0.1):

    res = np.empty(im.shape,im.dtype);

    t = cv2.max(t,tx);


    for ind in range(0,3):

    res[:,:,ind] = (im[:,:,ind]-A[0,ind])/t + A[0,ind]


    return res


if __name__ == '__main__':

    import sys

    try:

        fn = sys.argv[1]

    except:

        fn = 'demo.jpg'

    def nothing(*argv):

        pass

    src = cv2.imread(fn);

    I = src.astype('float64')/255;

    dark = DarkChannel(I,15);

    A = AtmLight(I,dark);

    te = TransmissionEstimate(I,A,15);

    t = TransmissionRefine(src,te);

    J = Recover(I,t,A,0.1);

    arr = np.hstack((I, J))

    cv2.imshow("contrast", arr)

    cv2.imwrite("dehaze.png", J*255 )

    cv2.imwrite("contrast.png", arr*255);

    cv2.waitKey();