暗通道去雾算法python

以下是一个简单的Python实现暗通道去雾算法的示例代码：

import numpy as np
import cv2

def dark_channel(img, size):
    b, g, r = cv2.split(img)
    dc = cv2.min(cv2.min(r, g), b)
    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (size, size))
    dark = cv2.erode(dc, kernel)
    return dark

def atm_light(img, dark):
    [h, w] = img.shape[:2]
    img_size = h * w
    numpx = int(max(np.floor(img_size / 1000), 1))
    darkvec = dark.reshape(img_size, 1)
    imvec = img.reshape(img_size, 3)
    indices = darkvec.argsort()[:img_size-numpx]
    atmsum = np.zeros([1, 3])
    for ind in range(len(indices)):
        atmsum = atmsum + imvec[indices[ind]]
    A = atmsum / (img_size-numpx)
    return A

def transmission_estimate(img, A, size):
    omega = 0.95
    im3 = np.zeros(img.shape)
    for ind in range(0, 3):
        im3[:, :, ind] = img[:, :, ind] / A[0, ind]
    transmission = 1 - omega * dark_channel(im3, size)
    return transmission

def guided_filter(p, i, r, eps):
    mean_i = cv2.boxFilter(i, cv2.CV_64F, (r, r))
    mean_p = cv2.boxFilter(p, cv2.CV_64F, (r, r))
    mean_ip = cv2.boxFilter(i*p, cv2.CV_64F, (r, r))
    cov_ip = mean_ip - mean_i*mean_p
    mean_ii = cv2.boxFilter(i*i, 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*i + mean_b
    return q

def refine_transmission(img, transmission):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = np.float64(gray) / 255
    r = 60
    eps = 0.0001
    t = guided_filter(gray, transmission, r, eps)
    return t

def recover(img, t, A, tx=0.1):
    res = np.empty(img.shape, img.dtype)
    t = cv2.max(t, tx)
    for ind in range(0, 3):
        res[:, :, ind] = (img[:, :, ind]-A[0, ind])/t + A[0, ind]
    return res

if __name__ == '__main__':
    img = cv2.imread('input.jpg')
    size = 15
    A = atm_light(img, dark_channel(img, size))
    transmission = transmission_estimate(img, A, size)
    transmission = refine_transmission(img, transmission)
    result = recover(img, transmission, A)
    cv2.imwrite('result.jpg', result)

其中，`dark_channel`函数用于计算暗通道图像，`atm_light`函数用于估计大气光照，`transmission_estimate`函数用于估计透射率，`guided_filter`函数用于引导滤波，`refine_transmission`函数用于细化透射率，`recover`函数用于恢复图像。

这段代码实现了暗通道去雾算法并将结果保存到`result.jpg`中。你可以将输入图像替换为你自己的图像，然后运行代码。注意，这段代码只是一个简单的示例，实际上应该根据图像的特点进行调整。