Relaxed median filter code
时间: 2023-06-28 16:16:07 浏览: 48
Here's an example implementation of the relaxed median filter in Python using the NumPy library:
```python
import numpy as np
from scipy.signal import medfilt2d
def relaxed_median_filter(image, size, threshold):
# Create a copy of the input image
filtered_image = np.copy(image)
# Calculate the radius of the filter window
radius = (size - 1) // 2
# Iterate over each pixel in the image
for i in range(radius, image.shape[0] - radius):
for j in range(radius, image.shape[1] - radius):
# Extract the window of neighboring pixels
window = image[i - radius:i + radius + 1, j - radius:j + radius + 1]
# Calculate the median value of the window
median = np.median(window)
# Calculate the range of values to consider
lower = median - threshold
upper = median + threshold
# Create a boolean mask of the pixels within the range
mask = np.logical_and(window >= lower, window <= upper)
# Calculate the median value of the pixels within the range
filtered_image[i, j] = np.median(window[mask])
return filtered_image
```
This implementation uses the `np.median` function to calculate the median value of the window, and then applies a threshold to determine which neighboring pixels to consider when calculating the filtered pixel value. The `scipy.signal.medfilt2d` function is used as a reference to handle edge cases.