jupyter notebooks写多通道彩色图像的SSIM代码
时间: 2023-07-25 19:14:15 浏览: 49
以下是一个示例代码,可以计算多通道彩色图像的 SSIM 值:
```python
import numpy as np
import cv2
def ssim(img1, img2):
# Set constants
C1 = (0.01 * 255) ** 2
C2 = (0.03 * 255) ** 2
# Convert the images to grayscale
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
# Compute mean, variance and covariance
img1_mean = cv2.mean(img1)[0]
img2_mean = cv2.mean(img2)[0]
img1_var = cv2.meanStdDev(img1)[1]**2
img2_var = cv2.meanStdDev(img2)[1]**2
img12_covar = np.mean((img1 - img1_mean) * (img2 - img2_mean))
# Compute SSIM
numerator = (2 * img1_mean * img2_mean + C1) * (2 * img12_covar + C2)
denominator = (img1_mean ** 2 + img2_mean ** 2 + C1) * (img1_var + img2_var + C2)
return numerator / denominator
# Load the images
img1 = cv2.imread('img1.png')
img2 = cv2.imread('img2.png')
# Compute SSIM
ssim_value = ssim(img1, img2)
print('SSIM value:', ssim_value)
```
你只需要将你的彩色图像读入 `img1` 和 `img2` 变量中,然后调用 `ssim` 函数即可计算它们的 SSIM 值。