信息熵,峰值信噪比评价图片彩色化质量代码
时间: 2023-11-12 09:00:05 浏览: 32
以下是一个简单的 Python 代码示例,用于计算图像的信息熵和峰值信噪比(PSNR)指标,以评估彩色化质量。需要安装 NumPy 和 OpenCV 库。
```python
import cv2
import numpy as np
# Load the original and colorized images (in BGR format)
img_original = cv2.imread('original.jpg')
img_colorized = cv2.imread('colorized.jpg')
# Calculate the image entropy
hist_original = cv2.calcHist([img_original], [0], None, [256], [0, 256])
hist_normalized = hist_original / float(img_original.size)
hist_normalized = hist_normalized[np.where(hist_normalized > 0)]
image_entropy = -np.sum(hist_normalized * np.log2(hist_normalized))
# Calculate the peak signal-to-noise ratio (PSNR)
mse = np.mean((img_original - img_colorized) ** 2)
if mse == 0:
psnr = 100
else:
psnr = 20 * np.log10(255.0 / np.sqrt(mse))
# Print the results
print("Image entropy:", image_entropy)
print("PSNR:", psnr)
```
其中,`img_original` 和 `img_colorized` 分别代表原始图像和彩色化后的图像,可以根据实际情况调整文件路径。输出结果包括图像的信息熵和 PSNR。