python估计有雾图像透射率图
时间: 2023-10-14 14:29:34 浏览: 36
可以使用以下代码估计有雾图像的透射率图:
```python
import cv2
import numpy as np
def estimate_transmission(img, block_size=15, w=0.95):
# Convert image to grayscale
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Compute minimum of 3 channels
min_channel = np.min(img.astype(np.float32), axis=2)
# Estimate dark channel
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (block_size, block_size))
dark_channel = cv2.erode(min_channel, kernel)
# Compute atmospheric light
num_pixels = dark_channel.size
num_top_pixels = int(num_pixels * w)
dark_channel_flat = dark_channel.ravel()
indices = np.argpartition(dark_channel_flat, -num_top_pixels)[-num_top_pixels:]
atmospheric_light = np.max(img_gray.ravel()[indices])
# Estimate transmission
transmission = 1 - w * (dark_channel / atmospheric_light)
# Clip transmission values
transmission = np.clip(transmission, 0, 1)
return transmission
```
其中,`img`是输入的有雾图像,`block_size`是计算暗通道时使用的块大小,`w`是透射率的权重。函数返回一个与输入图像大小相同的透射率图像。
使用示例:
```python
# Load image
img = cv2.imread('foggy_image.jpg')
# Estimate transmission
transmission = estimate_transmission(img)
# Display transmission map
cv2.imshow('Transmission', transmission)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
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