写出图片去雾，雨，雪的python代码

### 回答1：

答案：from PIL import Image
import numpy as np # 读取图片
img = Image.open('image.jpg') # 获取图片的宽度和高度
width, height = img.size# 将图片转换为灰度图
gray_img = img.convert('L')# 获取灰度图的像素值
pixels = gray_img.load() # 对每一个像素值进行去雾，雨，雪的处理
for x in range(width):
for y in range(height):
if pixels[x, y] > 100: # 对大于100的像素值进行处理
pixels[x, y] = 255 # 设置为255（白色）# 保存处理后的图片
gray_img.save('result.jpg')

### 回答2：
去雾的Python代码如下：

import cv2

def dehaze(image, t=0.1, w=0.95):
    # 计算导向滤波图像
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (9, 9), 0)
    gray = gray.astype('float32') / 255.0
    blur = blur.astype('float32') / 255.0
    
    difference = gray - blur
    
    # 计算大气光照
    (h, w) = gray.shape[:2]
    total_pixels = h * w
    pixels_to_keep = int(total_pixels * p)

    sorted_pixels = difference.ravel().argsort()

    max_index = sorted_pixels[-pixels_to_keep:]

    dark_channel = np.min(image, axis=2)
    dark_channel = dark_channel.astype('float32') / 255.0

    x, y = np.unravel_index(max_index, dark_channel.shape)
    max_channel = dark_channel[x, y]
    A = np.percentile(max_channel, 100 * w)

    # 计算透射率
    transmission = 1 - w * dark_channel / A
    
    # 优化透射率估计
    transmission = cv2.blur(transmission, (15, 15))
    
    # 修复图像
    result = np.empty_like(image)
    for i in range(3):
        result[:, :, i] = (image[:, :, i].astype('float32') - A) / transmission + A
    result = np.clip(result, 0, 1) * 255
    
    return result

image = cv2.imread('image.jpg')
dehazed_image = dehaze(image)
cv2.imshow('Dehazed Image', dehazed_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

其中，`image.jpg`是要去雾的图片路径。

下面是去雨的Python代码：

import cv2
import numpy as np

def derain(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    
    # 阈值分割得到雨滴区域
    _, binary_rain = cv2.threshold(gray, 230, 255, cv2.THRESH_BINARY)
    
    # 开运算去除细小雨滴
    kernel = np.ones((3, 3), np.uint8)
    rain_mask = cv2.morphologyEx(binary_rain, cv2.MORPH_OPEN, kernel, iterations=2)
    
    # 修复雨滴痕迹
    result = cv2.inpaint(image, rain_mask, 3, cv2.INPAINT_NS)
    
    return result

image = cv2.imread('image.jpg')
derained_image = derain(image)
cv2.imshow('Derained Image', derained_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

其中，`image.jpg`是要去雨的图片路径。

下面是去雪的Python代码：

import cv2
import numpy as np

def desnow(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    
    # 阈值分割得到雪花区域
    _, binary_snow = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY_INV)
    
    # 形态学操作去除细小雪花
    kernel = np.ones((3, 3), np.uint8)
    snow_mask = cv2.morphologyEx(binary_snow, cv2.MORPH_OPEN, kernel, iterations=2)
    
    # 修复雪花痕迹
    result = cv2.inpaint(image, snow_mask, 3, cv2.INPAINT_NS)
    
    return result

image = cv2.imread('image.jpg')
desnowed_image = desnow(image)
cv2.imshow('Desnowed Image', desnowed_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

其中，`image.jpg`是要去雪的图片路径。