DCP暗通道python

DCP暗通道python实现的代码可以参考以下示例：

import cv2
import numpy as np

def get_min_channel(img):
    return np.min(img, axis=2)

def guided_filter(I, p, win_size, eps):
    mean_I = cv2.blur(I, (win_size, win_size))
    mean_p = cv2.blur(p, (win_size, win_size))
    corr_I = cv2.blur(I*I, (win_size, win_size))
    corr_Ip = cv2.blur(I*p, (win_size, win_size))
    var_I = corr_I - mean_I * mean_I
    cov_Ip = corr_Ip - mean_I * mean_p
    a = cov_Ip / (var_I + eps)
    b = mean_p - a * mean_I
    mean_a = cv2.blur(a, (win_size, win_size))
    mean_b = cv2.blur(b, (win_size, win_size))
    q = mean_a * I + mean_b
    return q

def get_A(img_haze, dark_channel, bins_l):
    hist, bins = np.histogram(dark_channel, bins=bins_l)
    d = np.cumsum(hist) / float(dark_channel.size)
    threshold = 0
    for i in range(bins_l-1, 0, -1):
        if d[i <= 0.999:
            threshold = i
            break
    A = img_haze[dark_channel >= bins<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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