问题
I am trying to find some relative maximums of a given image. I understand that there are two possible methods, the first is using scipy.ndimage.maximum_filter() and the second using skimage.feature.peak_local_max().
In order to compare both methods I have modified an example from skimage shown here in order to compare the peaks found.
from scipy import ndimage as ndi
import matplotlib.pyplot as plt
from skimage.feature import peak_local_max
from skimage import data, img_as_float
im = img_as_float(data.coins())
# use ndimage to find the coordinates of maximum peaks
image_max = ndi.maximum_filter(im, size=20) == im
j, i = np.where(image_max)
coordinates_2 = np.array(zip(i,j))
# use skimage to find the coordinates of local maxima
coordinates = peak_local_max(im, min_distance=20)
# display results
fig, axes = plt.subplots(1, 2, figsize=(8, 3), sharex=True, sharey=True)
ax = axes.ravel()
ax[0].imshow(im, cmap=plt.cm.gray)
ax[0].plot(coordinates_2[:, 0], coordinates_2[:, 1], 'r.')
ax[0].axis('off')
ax[0].set_title('Maximum filter')
ax[1].imshow(im, cmap=plt.cm.gray)
ax[1].autoscale(False)
ax[1].plot(coordinates[:, 1], coordinates[:, 0], 'r.')
ax[1].axis('off')
ax[1].set_title('Peak local max')
fig.tight_layout()
plt.show()
This gives the next peaks for each method:
I understand that the parameter size for maximum_filter is not equivalent to the min_distance from peak_local_max, but I'd like to know if there is a method in which both give the same result. Is that possible?
Some related question on stackoverflow are:
Get coordinates of local maxima in 2D array above certain value
Peak detection in a 2D array
来源：https://stackoverflow.com/questions/56148387/finding-image-peaks-using-ndimage-maximum-filter-and-skimage-peak-local-max